Search results for: monitoring network optimization

Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

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Authors: Mourad Hrizi

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In this paper, we study the inverse problem of reconstructing an interior interface D appearing in the elliptic partial differential equation: Δu+χ(D)u=0 from the knowledge of the boundary measurements. This problem arises from a semiconductor transistor model. We propose a new shape reconstruction procedure that is based on the Kohn-Vogelius formulation and the topological sensitivity method. The inverse problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a function. The unknown subdomain D is reconstructed using a level-set curve of the topological gradient. Finally, we give several examples to show the viability of our proposed method.

Keywords: inverse problem, topological optimization, topological gradient, Kohn-Vogelius formulation

Procedia PDF Downloads 242

Authors: E. Behmanesh, J. Pannek

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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

Procedia PDF Downloads 186

Authors: Mallikarjun B. Channappagoudar, Pallapa Venkataram

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The dynamic nature of Mobile adhoc network (MANET) due to mobility and disconnection of mobile nodes, leads to various problems in predicting the movement of nodes and their location information updation, for efficient interaction among the application specific nodes. Location management is one of the main challenges to be considered for an efficient service provision to the applications of a MANET. In this paper, we propose a location management protocol, for locating the nodes of a MANET and to maintain uninterrupted high-quality service for distributed applications by intelligently anticipating the change of location of its nodes. The protocol predicts the node movement and application resource scarcity, does the replacement with the chosen nodes nearby which have less mobility and rich in resources, with the help of both static and mobile agents, and maintains the application continuity by providing required network resources. The protocol has been simulated using Java Agent Development Environment (JADE) Framework for agent generation, migration and communication. It consumes much less time (response time), gives better location accuracy, utilize less network resources, and reduce location management overhead.

Keywords: mobile agent, location management, distributed applications, mobile adhoc network

Procedia PDF Downloads 393

Authors: Hind Mohammed A. Asiri, Asia Mohammed Asiri, Hana Falah Alruwaili, Joseph Almazan

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With the rapid growth of the older adult population, an underlying growth of public health concern is also seen. Various technologies were developed to help mitigate the arising problems of older adults with cognitive impairment and the improvement of their cognitive functions. This scooping review used the Joanna Briggs Institute (JBI) and the PRISMA extension for scoping reviews. The eligibility criteria were defined using the Population, Concept, Context (PCC) framework, as described in the JBI’s Reviewers Manual (Peters et al.,2020). The population of interest for this review is older adults 65 years old or older. Studies involving monitoring technology devices utilized in caring with older adult with cognitive impairment. This scoping review has shown information that researchers are more focused on creating alternative and novel methods or technological devices and use these as a tool for designing interventions depending on the data of the patient. This study has shown the type of technologies that have been explored in terms of assessing, detecting, monitoring, and interventions for cognitive impairment. Thus, there is a need for this technology to be applied in the practical field to further strengthen the evidence that it could enhance the lives of older adults.

Keywords: technology devices, cognitive impairment, older adult, nursing care, caring

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Authors: C. N. Okafor, M. Maaza, T. A. E. Mokrani

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A proton exchange membrane has been developed for Direct Methanol Fuel Cell (DMFC). The nanofiber network composite membranes were prepared by interconnected network of Nafion (perfuorosulfonic acid) nanofibers that have been embedded in an uncharged and inert polymer matrix, by electro-spinning. The spinning solution of Nafion with a low concentration (1 wt. % compared to Nafion) of high molecular weight poly(ethylene oxide), as a carrier polymer. The interconnected network of Nafion nanofibers with average fiber diameter in the range of 160-700nm, were used to make the membranes, with the nanofiber occupying up to 85% of the membrane volume. The matrix polymer was cross-linked with Norland Optical Adhesive 63 under UV. The resulting membranes showed proton conductivity of 0.10 S/cm at 25°C and 80% RH; and methanol permeability of 3.6 x 10-6 cm2/s.

Keywords: composite membrane, electrospinning, fuel cell, nanofibers

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Authors: Karthikeyan Kalirajan, Ashok Joshi

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An optimization problem is to setup to maximize the terminal kinetic energy of a maneuverable reentry vehicle (MaRV). The target location, the impact angle is given as constraints. The MaRV uses an explicit guidance law called Vector guidance. This law has two gains which are taken as decision variables. The problem is to find the optimal value of these gains which will result in minimum miss distance and impact angle error. Using a simple 3DOF non-rotating flat earth model and Lockheed martin HP-MARV as the reentry vehicle, the nature of solutions of the optimization problem is studied. This is achieved by carrying out a parametric study for a range of closed loop gain values and the corresponding impact angle error and the miss distance values are generated. The results show that there are well defined lower and upper bounds on the gains that result in near optimal terminal guidance solution. It is found from this study, that there exist common permissible regions (values of gains) where all constraints are met. Moreover, the permissible region lies between flat regions and hence the optimization algorithm has to be chosen carefully. It is also found that, only one of the gain values is independent and that the other dependent gain value is related through a simple straight-line expression. Moreover, to reduce the computational burden of finding the optimal value of two gains, a guidance law called Diveline guidance is discussed, which uses single gain. The derivation of the Diveline guidance law from Vector guidance law is discussed in this paper.

Keywords: Marv guidance, reentry trajectory, trajectory optimization, guidance gain selection

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Authors: C. Lanzerstorfer

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Liquid sprays of water are frequently used in air pollution control for gas cooling purposes and for gas cleaning. Twin-fluid nozzles with internal mixing are often used for these purposes because of the small size of the drops produced. In these nozzles the liquid is dispersed by compressed air or another pressurized gas. In high efficiency scrubbers for particle separation, several nozzles are operated in parallel because of the size of the cross section. In such scrubbers, the scrubbing water has to be re-circulated. Precipitation of some solid material can occur in the liquid circuit, caused by chemical reactions. When such precipitations are detached from the place of formation, they can partly or totally block the liquid flow to a nozzle. Due to the resulting unbalanced supply of the nozzles with water and gas, the efficiency of separation decreases. Thus, the nozzles have to be cleaned if a certain fraction of blockages is reached. The aim of this study was to provide a tool for continuously monitoring the status of the nozzles of a scrubber based on the available operation data (water flow, air flow, water pressure and air pressure). The difference between the air pressure and the water pressure is not well suited for this purpose, because the difference is quite small and therefore very exact calibration of the pressure measurement would be required. Therefore, an equation for the reference air flow of a nozzle at the actual water flow and operation pressure was derived. This flow can be compared with the actual air flow for assessment of the status of the nozzles.

Keywords: condition monitoring, dual flow nozzles, flow equation, operation data

Procedia PDF Downloads 264

Authors: Maoxin Ye

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This study examines the relationship between social network sites (SNS) usage and social capital. Because SNS usage can expand the users’ networks, and people who are connected in this networks may become resources to SNS users and lead them to advantage in some situation, it is important to estimate the relationship between SNS usage and ‘who’ is connected or what resources the SNS users can get. Additionally, ‘who’ can be divided in two aspects – people who possess high position and people who are different, hence, it is important to estimate the relationship between SNS usage and high position people and different people. This study adapts Lin’s definition of social capital and the measurement of position generator which tells us who was connected, and can be divided into the same two aspects as well. A national data of America (N = 2,255) collected by Pew Research Center is utilized to do a general regression analysis about SNS usage and social capital. The results indicate that SNS usage is negatively associated with each factor of social capital, and it suggests that, in fact, comparing with non-users, although SNS users can get more connections, the variety and resources of these connections are fewer. For this reason, we could lose benefits through SNS usage.

Keywords: social network sites, social capital, position generator, general regression

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Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

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Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: identification, Hammerstein-Wiener, optimization, quantization

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: M. Nekri, A. Khelladi

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The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

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Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

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Authors: Dêivisson Alves Anjos, Blenda Fonseca Aires Teles, Queitiane Castro Costa

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Fire is one of the biggest dangers for factories, warehouses, mills, among other places, causing unimaginable damage, because besides the material damage also directly affects the lives of workers who are likely to suffer death or very serious consequences. This protection of the lives of these people should be taken seriously, always seeking safety. Thus investment in security and monitoring equipment must be high, so you can prevent or reduce the impacts of a possible fire. Our device, made in PIC micro controller monitors the temperature and the presence of gas in the environment, it sends the data via Bluetooth device to a developed in LabVIEW interface saves these data continuously and alert if the temperature exceeds the allowed or some gas is detected. Currently the device is in operation and can perform several tests, as well as use in different areas for which you need anti-fire protection.

Keywords: pic, bluetooth, fire, temperature, gas, LabVIEW

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Authors: Ghita Benayad

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Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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Authors: Hamidoddin Yousife

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Drilling optimization requires a prediction of drilling rate of penetration (ROP) since it provides a significant reduction in drilling costs. There are several factors that can have an impact on the ROP, both controllable and uncontrollable. Numerous drilling penetration rate models have been considered based on drilling parameters. This papers considered the effect of proper drilling parameter selection such as bit, Mud Type, applied weight on bit (WOB), Revolution per minutes (RPM), and flow rate on drilling optimization and drilling cost reduction. A predicted analysis is used in real-time drilling performance to determine the optimal drilling operation. As a result of these modeling studies, the real data collected from three directional wells at Azadegan oil fields, Iran, was verified and adjusted to determine the drillability of a specific formation. Simulation results and actual drilling results show significant improvements in inaccuracy. Once simulations had been validated, optimum drilling parameters and equipment specifications were determined by varying weight on bit (WOB), rotary speed (RPM), hydraulics (hydraulic pressure), and bit specification for each well until the highest drilling rate was achieved. To evaluate the potential operational and economic benefits of optimizing results, a qualitative and quantitative analysis of the data was performed.

Keywords: drlling, cost, optimization, parameters

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Authors: Innocent Uzougbo Onwuegbuzie

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Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.

Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security

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Authors: Ameen Jameel Alawneh

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A Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts that dynamically form a temporary network without the aid of a system administrator. It has neither fixed infrastructure nor wireless ad hoc sessions. It inherently reaches several nodes with a single transmission, and each node functions as both a host and a router. The network maybe represented as a set of clusters each managed by clusterhead. The cluster size is not fixed and it depends on the movement of nodes. We proposed a clusterhead size algorithm (CHSize). This clustering algorithm can be used by several routing algorithms for ad hoc networks. An elected clusterhead is assigned for communication with all other clusters. Analysis and simulation of the algorithm has been implemented using GloMoSim networks simulator, MATLAB and MAPL11 proved that the proposed algorithm achieves the goals.

Keywords: simulation, MANET, Ad-hoc, cluster head size, linked cluster algorithm, loss and dropped packets

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Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

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Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

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Authors: Laaziz El Hassan

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The Service Network Design Problem (SNDP) is a tactical issue in freight transportation firms. The existing formulations of the problem for intermodal rail-road transportation were not always adapted to the intermodality in terms of full asset utilization and modal shift reinforcement. The objective of the article is to propose a model having a more compliant formulation with intermodality, including constraints highlighting the imperatives of asset management, reinforcing modal shift from road to rail and reducing, by the way, road mode CO2 emissions. The model is a fixed charged, path based integer nonlinear program. Its objective is to minimize services total cost while ensuring full assets utilization to satisfy freight demand forecast. The model's main feature is that it gives as output both the train sizes and the services frequencies for a planning period. We solved the program using a commercial solver and discussed the numerical results.

Keywords: intermodal transport network, service network design, model, nonlinear integer program, path-based, service frequencies, modal shift

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Authors: Andrey A. Chernousov, Ben Y. B. Chan

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The use of the low-cost paraffinic phase change material can be rather effective in smart building envelopes in the South China region. Particular attention has to be paid to the PCM optimization as an exploitation conditions and the envelope insulation changes its thermal characteristics. The studied smart building envelope consists of a reinforced aluminum exterior, polymeric insulation foam, phase change material and reinforced interior gypsum board. A prototype sample was tested to validate the numerical scheme using EnergryPlus software. Three scenarios of insulation thermal resistance loss (ΔR/R = 0%, 25%, 50%) were compared with the different PCM thicknesses (tP=0, 1, 2.5, 5 mm). The comparisons were carried out for a west facing enveloped office building (50 storey). PCM optimization was applied to find the maximum efficiency for the different ΔR/R cases. It was found, during the optimization, that the PCM is an important smart component, lowering the peak energy demand up to 2.7 times. The results are not influenced by the insulation aging in terms of ΔR/R during long-term exploitation. In hot and humid climates like Hong Kong, the insulation core of the smart systems is recommended to be laminated completely. This can be very helpful in achieving an acceptable payback period.

Keywords: smart building envelope, thermal performance, phase change material, energy efficiency, large-scale sandwich panel

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Authors: Kevin Spencer G. Anglim, Zhenyu Zhang, Qingbin Gao

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Reusable launch vehicles (RLVs) present a more environmentally-friendly approach to accessing space when compared to traditional launch vehicles that are discarded after each flight. This paper studies the recyclable nature of RLVs by presenting a solution method for determining minimum-fuel optimal trajectories using principles from optimal control theory and particle swarm optimization (PSO). This problem is formulated as a minimum-landing error powered descent problem where it is desired to move the RLV from a fixed set of initial conditions to three different sets of terminal conditions. However, unlike other powered descent studies, this paper considers the highly nonlinear effects caused by atmospheric drag, which are often ignored for studies on the Moon or on Mars. Rather than optimizing the controls directly, the throttle control is assumed to be bang-off-bang with a predetermined thrust direction for each phase of flight. The PSO method is verified in a one-dimensional comparison study, and it is then applied to the two-dimensional cases, the results of which are illustrated.

Keywords: minimum-fuel optimal trajectory, particle swarm optimization, reusable rocket, SpaceX

Procedia PDF Downloads 277

Authors: Jiwon Park, Jihae Hur, Kukjae Kim, Hansoo Kim

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In this study, outriggers, which are horizontal structures connecting a building core to distant columns to increase the lateral stiffness of a tall building, are used to reduce differential axial shortening in a tall building. Therefore, the outriggers in tall buildings are used to serve the dual purposes of reducing the lateral displacement and reducing the differential axial shortening. Since the location of the outrigger greatly affects the effectiveness of the outrigger in terms of the lateral displacement at the top of the tall building and the maximum differential axial shortening, the optimum locations of the dual-purpose outriggers can be determined by an optimization method. Because the floors where the outriggers are installed are given as integer numbers, the conventional gradient-based optimization methods cannot be directly used. In this study, a piecewise quadratic interpolation method is used to resolve the integrality requirement posed by the optimum locations of the dual-purpose outriggers. The optimal solutions for the dual-purpose outriggers are searched by linear scalarization which is a popular method for multi-objective optimization problems. It was found that increasing the number of outriggers reduced the maximum lateral displacement and the maximum differential axial shortening. It was also noted that the optimum locations for reducing the lateral displacement and reducing the differential axial shortening were different. Acknowledgment: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (NRF-2017R1A2B4010043) and financially supported by Korea Ministry of Land, Infrastructure and Transport(MOLIT) as U-City Master and Doctor Course Grant Program.

Keywords: concrete structure, optimization, outrigger, tall building

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Authors: Qasim Khan, Furkan Ahmad, Asfar A. Khan, M. Saad Alam, Faiz Ahmad

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In this paper, partial discharge analysis is performed in cavities artificially created in insulation. The setup is according with Cigre-II Method. Circular Samples created from Perspex Sheet with different configuration with changing number of cavities. Assessment of insulation health can be performed by Partial Discharge measurement as this has been found to be important means of condition monitoring. The experiments are done using MPD 540, which is a modern partial discharge measurement system. By analyzing the PD activity obtained for various voids/cavities, it is observed that the PD voltages show variation for cavity’s diameter, depth even for its ratios. This can be employed for scrutiny of insulation system.

Keywords: partial discharges, condition monitoring, insulation defects, degradation and corrosion, PMMA

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Authors: Angela U. Makolo, Temitayo A. Olagunju

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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.

Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways

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Authors: Chia-Chen Chen, Mu-Yen Chen

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In recent years, with the vigorous growth of hardware and software technologies of smart mobile devices coupling with the rapid increase of social network influence, mobile commerce also presents the commercial operation mode of the future mainstream. For the time being, SoLoMo has become one of the very popular commercial models, its full name and meaning mainly refer to that users can obtain three key service types through smart mobile devices (Mobile) and omnipresent network services, and then link to the social (Social) web site platform to obtain the information exchange, again collocating with position and situational awareness technology to get the service suitable for the location (Local), through anytime, anywhere and any personal use of different mobile devices to provide the service concept of seamless integration style, and more deriving infinite opportunities of the future. The study tries to explore the use intention of users with SoLoMo mobile application formula, proposing research model to integrate TAM, ISSM, IDT and network externality, and with questionnaires to collect data and analyze results to verify the hypothesis, results show that perceived ease-of-use (PEOU), perceived usefulness (PU), and network externality have significant impact on the use intention with SoLoMo mobile application formula, and the information quality, relative advantages and observability have impacts on the perceived usefulness, and further affecting the use intention.

Keywords: SoLoMo (social, local, and mobile), technology acceptance model, innovation diffusion theory, network externality

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

Abstract:

State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Lea B. Milan

Abstract:

This descriptive study evaluated the existing Food Safety Management in Central Elementary School Canteens of Region 3. It made used of survey questionnaires, interview guide questions and validated knowledge test on food for data gathering. Results of the study revealed that school principals and canteen managers shared responsibilities in food safety management of school canteen. It also showed that the schools applied different methods of communication, monitoring and evaluation of food safety management. The study further revealed that implementation of monitoring and evaluation of food safety compliance are not being practiced in all elementary schools in the region. The study also showed that school canteens in the Region 3 do not have the thermometers and timers to use to conduct proper monitoring of foods during storage, preparation and serving. It was also found out from the study that canteen personnel lacks the basic knowledge and trainings on food safety. Potential source of physical, chemical and biological hazards that could contaminate foods were also found present in the canteen facilities of the elementary schools in the region. Moreover, evaluation showed that the existing implementation of food safety management in the Central Elementary School Canteens of Region 3 were below the expected level and the need to strengthen the appreciation and advocacy on food safety management in school canteens of Region 3 is still wanting.

Keywords: food safety management, food safety school catering, food safety, school food safety management

Procedia PDF Downloads 375

Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

Abstract:

Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

Procedia PDF Downloads 112