Search results for: wireless networks simulation

Authors: Lyndsee Baumann-Birkbeck, Sohil A. Khan, Shailendra Anoopkumar-Dukie, Gary D. Grant

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Technology-enhanced education tools are being rapidly integrated into health programs globally. These tools provide an interactive platform for students and can be used to deliver topics in various modes including games and simulations. Simulations are of particular interest to healthcare education, where they are employed to enhance clinical knowledge and help to bridge the gap between theory and practice. Simulations will often assess competencies for practical tasks, yet limited research examines the effects of simulation on student perceptions of their learning. The aim of this study was to determine the effects of an interactive virtual patient simulation for pharmacology education and clinical practice on student knowledge, skills and confidence. Ethics approval for the study was obtained from Griffith University Research Ethics Committee (PHM/11/14/HREC). The simulation was intended to replicate the pharmacy environment and patient interaction. The content was designed to enhance knowledge of proton-pump inhibitor pharmacology, role in therapeutics and safe supply to patients. The tool was deployed into a third-year clinical pharmacology and therapeutics course. A number of core practice areas were examined including the competency domains of questioning, counselling, referral and product provision. Baseline measures of student self-reported knowledge, skills and confidence were taken prior to the simulation using a specifically designed questionnaire. A more extensive questionnaire was deployed following the virtual patient simulation, which also included measures of student engagement with the activity. A quiz assessing student factual and conceptual knowledge of proton-pump inhibitor pharmacology and related counselling information was also included in both questionnaires. Sixty-one students (response rate >95%) from two cohorts (2014 and 2015) participated in the study. Chi-square analyses were performed and data analysed using Fishers exact test. Results demonstrate that student knowledge, skills and confidence within the competency domains of questioning, counselling, referral and product provision, show improvement following the implementation of the virtual patient simulation. Statistically significant (p<0.05) improvement occurred in ten of the possible twelve self-reported measurement areas. Greatest magnitude of improvement occurred in the area of counselling (student confidence p<0.0001). Student confidence in all domains (questioning, counselling, referral and product provision) showed a marked increase. Student performance in the quiz also improved, demonstrating a 10% improvement overall for pharmacology knowledge and clinical practice following the simulation. Overall, 85% of students reported the simulation to be engaging and 93% of students felt the virtual patient simulation enhanced learning. The data suggests that the interactive virtual patient simulation developed for clinical pharmacology and therapeutics education enhanced students knowledge, skill and confidence, with respect to the competency domains of questioning, counselling, referral and product provision. These self-reported measures appear to translate to learning outcomes, as demonstrated by the improved student performance in the quiz assessment item. Future research of education using virtual simulation should seek to incorporate modern quantitative measures of student learning and engagement, such as eye tracking.

Keywords: clinical simulation, education, pharmacology, simulation, virtual learning

Procedia PDF Downloads 336

Authors: Sekkal Nawel

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The Web of Things (WoT), integration of smart technologies from the Internet or network to Web architecture or application, is becoming more complex, larger, and dynamic. The WoT is associated with various elements such as sensors, devices, networks, protocols, data, functionalities, and architectures to perform services for stakeholders. These services operate in the context of the interaction of stakeholders and the WoT elements. Such context is becoming a key information source from which data are of various nature and uncertain, thus leading to complex situations. In this paper, we take interest in the development of intelligent Web services. The key ingredients of this “intelligent” notion are the context diversity, the necessity of a semantic representation to manage complex situations and the capacity to reason with uncertain data. In this perspective, we introduce a multi-layered architecture based on a generic intelligent Web service model dealing with various contexts, which proactively predict future situations and reactively respond to real-time situations in order to support decision-making. For semantic context data representation, we use PR-OWL, which is a probabilistic ontology based on Multi-Entity Bayesian Networks (MEBN). PR-OWL is flexible enough to represent complex, dynamic, and uncertain contexts, the key requirements of the development for the intelligent Web services. A case study was carried out using the proposed architecture for intelligent plant watering to show the role of proactive and reactive contextual reasoning in terms of WoT.

Keywords: smart web service, the web of things, context reasoning, proactive, reactive, multi-entity bayesian networks, PR-OWL

Procedia PDF Downloads 70

Authors: Lior Davidovitch

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Traditional training based on static models and case studies is the backbone of most teaching and training programs of engineering education. However, project management learning is characterized by dynamics models that requires new and enhanced learning method. The results of empirical experiments evaluating the effectiveness and efficiency of using cognitive simulator as a new training technique are reported. The empirical findings are focused on the impact of keeping and reviewing learning history in a dynamic and interactive simulation environment of engineering education. The cognitive simulator for engineering project management learning had two learning history keeping modes: manual (student-controlled), automatic (simulator-controlled) and a version with no history keeping. A group of industrial engineering students performed four simulation-runs divided into three identical simple scenarios and one complicated scenario. The performances of participants running the simulation with the manual history mode were significantly better than users running the simulation with the automatic history mode. Moreover, the effects of using the undo enhanced further the learning process. The findings indicate an enhancement of engineering students’ learning and decision making when they use the record functionality of the history during their engineering training process. Furthermore, the cognitive simulator as educational innovation improves students learning and training. The practical implications of using simulators in the field of engineering education are discussed.

Keywords: cognitive simulator, decision making, engineering learning, project management

Procedia PDF Downloads 247

Authors: H. Parveen Begam, M. A. Maluk Mohamed

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Mobile Grid Computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using different types of electronic portable devices. In a grid environment the security issues are like authentication, authorization, message protection and delegation handled by GSI (Grid Security Infrastructure). Proving better security between mobile devices and grid infrastructure is a major issue, because of the open nature of wireless networks, heterogeneous and distributed environments. In a mobile grid environment, the individual computing devices may be resource-limited in isolation, as an aggregated sum, they have the potential to play a vital role within the mobile grid environment. Some adaptive methodology or solution is needed to solve the issues like authentication of a base station, security of information flowing between a mobile user and a base station, prevention of attacks within a base station, hand-over of authentication information, communication cost of establishing a session key between mobile user and base station, computing complexity of achieving authenticity and security. The sharing of resources of the devices can be achieved only through the trusted relationships between the mobile hosts (MHs). Before accessing the grid service, the mobile devices should be proven authentic. This paper proposes the dynamic certificate based mutual authentication protocol between two mobile hosts in a mobile grid environment. The certificate generation process is done by CA (Certificate Authority) for all the authenticated MHs. Security (because of validity period of the certificate) and dynamicity (transmission time) can be achieved through the secure service certificates. Authentication protocol is built on communication services to provide cryptographically secured mechanisms for verifying the identity of users and resources.

Keywords: mobile grid computing, certificate authority (CA), SSL/TLS protocol, secured service certificates

Procedia PDF Downloads 305

Authors: Seunghee Park, Junkyeong Kim, Eun-Seok Shin, Sang-Hun Han

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In this study, two kinds of nondestructive evaluation (NDE) techniques (rebound hardness and ultrasonic pulse velocity methods) are investigated for the effective maintenance of underwater concrete structures. A new methodology to estimate the underwater concrete strengths more effectively, named “artificial neural network (ANN) – based concrete strength estimation with the combination of rebound hardness and ultrasonic pulse velocity methods” is proposed and verified throughout a series of experimental works.

Keywords: underwater concrete, rebound hardness, Schmidt hammer, ultrasonic pulse velocity, ultrasonic sensor, artificial neural networks, ANN

Procedia PDF Downloads 530

Authors: Gondu Vykunta Rao, Madhuri Bayya, Aruna Bharathi M., Paramesw Chidamparam, B. Murali

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The increase in software content in today’s electric vehicles is increasing attention to having vast, unique topographies from low emission to high efficiency, whereas the chemical batteries have huge short comes, such as limited cycle life, power density, and cost. As for understanding and visualization, the companies are turning toward the virtual vehicle to test their design in software which is known as a simulation in the loop (SIL). In this project, in addition to the electric vehicle (EV) technology, we are adding a dynamo with the vehicle for regenerative braking. Traditionally the principle of dynamos is used in lighting the purpose of the bicycle. Here by using the same mechanism, we are running the vehicle as well as charging the vehicle from system-level simulation to the model in the loop and then to the Hardware in Loop (HIL) by using model-based development.

Keywords: electric vehicle, simulation in the loop (SIL), model in loop (MIL), hardware in loop (HIL), dynamos, model-based development (MBD), permanent magnet synchronous motor (PMSM), current control (CC), field-oriented control (FOC), regenerative braking

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Authors: Vladimir S. Timofeev

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In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique, author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.

Keywords: characteristic function, distributional moments, robustness, outlier, statistical estimation problem, statistical simulation

Procedia PDF Downloads 502

Authors: Cristina Chaminade, Mandar Kulkarni, Balaji Parthasarathy, Monica Plechero

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The characteristics of a regional innovation system (RIS) and the specificity of the knowledge base of an industry may contribute to create peculiar paths for innovation and development of firms’ geographic extended innovation networks. However, the relative empirical evidence in emerging economies remains underexplored. The paper aims to fill the research gap by means of some recent qualitative research conducted in 2016 in Beijing (China) and Bangalore (India). It analyzes cases studies of firms in the new media industry, a sector that merges different IT competences with competences from other knowledge domains and that is emerging in those RIS. The results show that while in Beijing the new media sector results to be more in line with the existing institutional setting and governmental goals aimed at targeting specific social aspects and social problems of the population, in Bangalore it remains a more spontaneous firms-led process. In Beijing what matters for the development of innovation networks is the governmental setting and the national and regional strategies to promote science and technology in this sector, internet and mass innovation. The peculiarities of recent governmental policies aligned to the domestic goals may provide good possibilities for start-ups to develop innovation networks. However, due to the specificities of those policies targeting the Chinese market, networking outside the domestic market are not so promoted. Moreover, while some institutional peculiarities, such as a culture of collaboration in the region, may be favorable for local networking, regulations related to Internet censorship may limit the use of global networks particularly when based on virtual spaces. Mainly firms with already some foreign experiences and contact take advantage of global networks. In Bangalore, the role of government in pushing networking for the new media industry at the present stage is quite absent at all geographical levels. Indeed there is no particular strategic planning or prioritizing in the region toward the new media industry, albeit one industrial organization has emerged to represent the animation industry interests. This results in a lack of initiatives for sustaining the integration of complementary knowledge into the local portfolio of IT specialization. Firms actually involved in the new media industry face institutional constrains related to a poor level of local trust and cooperation, something that does not allow for full exploitation of local linkages. Moreover, knowledge-provider organizations in Bangalore remain still a solid base for the IT domain, but not for other domains. Initiatives to link to international networks seem therefore more the result of individual entrepreneurial actions aimed at acquiring complementary knowledge and competencies from different domains and exploiting potentiality in different markets. From those cases, it emerges that role of government, soft institutions and organizations in the two RIS differ substantially in the creation of barriers and opportunities for the development of innovation networks and their specific aim.

Keywords: regional innovation system, emerging economies, innovation network, institutions, organizations, Bangalore, Beijing

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Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

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Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

Procedia PDF Downloads 150

Authors: Toufik Karech, Abderahmen Benseghir, Tayeb Bouzid

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This work presents a 2D numerical simulation of an earth dam to assess the behavior of its foundation after a treatment by stone columns. This treatment aims to improve the bearing capacity, to increase the mechanical properties of the soil, to accelerate the consolidation, to reduce the settlements and to eliminate the liquefaction phenomenon in case of seismic excitation. For the evaluation of the pore pressures, the position of the phreatic line and the flow network was defined, and a seepage analysis was performed with the software MIDAS Soil Works. The consolidation calculation is performed through a simulation of the actual construction stages of the dam. These analyzes were performed using the Mohr-Coulomb soil model and the results are compared with the actual measurements of settlement gauges implanted in the dam. An analysis of the bearing capacity was conducted to show the role of stone columns in improving the bearing capacity of the foundation.

Keywords: earth dam, dam foundation, numerical simulation, stone columns, seepage analysis, consolidation, bearing capacity

Procedia PDF Downloads 189

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

Procedia PDF Downloads 642

Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

Procedia PDF Downloads 365

Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI

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Authors: Lea Lenhardt, Ivana Zeković, Tatjana Dramićanin, Miroslav D. Dramićanin

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Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) and artificial neural networks (ANN) were used for characterization and classification of honey. Excitation emission spectra were obtained for 95 honey samples of different botanical origin (acacia, sunflower, linden, meadow, and fake honey) by recording emission from 270 to 640 nm with excitation in the range of 240-500 nm. Fluorescence spectra were described with a six-component PARAFAC model, and PARAFAC scores were further processed with two types of ANN’s (feed-forward network and self-organizing maps) to obtain algorithms for classification of honey on the basis of their botanical origin. Both ANN’s detected fake honey samples with 100% sensitivity and specificity.

Keywords: honey, fluorescence, PARAFAC, artificial neural networks

Procedia PDF Downloads 953

Authors: Redhouane Ghernaout, Amira Fredj, Boualem Remini

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Suspended sediment transport is a serious problem worldwide, but it is much more worrying in certain regions of the world, as is the case in the Maghreb and more particularly in Algeria. It continues to take disturbing proportions in Northern Algeria due to the variability of rains in time and in space and constant deterioration of vegetation. Its prediction is essential in order to identify its intensity and define the necessary actions for its reduction. The purpose of this study is to analyze the concentration data of suspended sediment measured at Wadi El-Abtal Hydrometric Station. It also aims to find and highlight regressive power relationships, which can explain the suspended solid flow by the measured liquid flow. The study strives to find models of artificial neural networks linking the flow, month and precipitation parameters with solid flow. The obtained results show that the power function of the solid transport rating curve and the models of artificial neural networks are appropriate methods for analysing and estimating suspended sediment transport in Wadi Mina at Wadi El-Abtal Hydrometric Station. They made it possible to identify in a fairly conclusive manner the model of neural networks with four input parameters: the liquid flow Q, the month and the daily precipitation measured at the representative stations (Frenda 013002 and Ain El-Hadid 013004 ) of the watershed. The model thus obtained makes it possible to estimate the daily solid flows (interpolate and extrapolate) even beyond the period of observation of solid flows (1985/86 to 1999/00), given the availability of the average daily liquid flows and daily precipitation since 1953/1954.

Keywords: suspended sediment, concentration, regression, liquid flow, solid flow, artificial neural network, modeling, mina, algeria

Procedia PDF Downloads 99

Authors: Mohammad Derakhshani, Saeed Reza Allahkaram, Michael Isakani-Zakaria, Masoud Samadian, Hojat Sharifi Rasaey

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Dynamic stray currents tend to change their magnitude and polarity with time at their source which will create anodic and cathodic spots on a nearby interfered structure. To date, one of the biggest known dynamic stray current sources are DC traction systems. Laboratory simulation is a suitable method to apply theoretical principles in order to identify effective parameters in dynamic stray current influenced corrosion. Simulation techniques can be utilized for various mitigation methods applied in a small scales for selection of the most efficient method with regards to field applications. In this research, laboratory simulation of potential fluctuations caused by dynamic stray current on a cathodically protected structure was investigated. A lab model capable of generating DC static and dynamic stray currents and simulating its effects on cathodically protected samples were developed based on stray current induced (contact-less) polarization technique. Stray current pick-up and discharge spots on an influenced structure were simulated by inducing fluctuations in the sample’s stationary potential. Two mitigation methods for dynamic stray current interference on buried structures namely application of sacrificial anodes as preferred discharge point for the stray current and potentially controlled cathodic protection was investigated. Results showed that the application of sacrificial anodes can be effective in reducing interference only in discharge spot. But cathodic protection through potential controlling is more suitable for mitigating dynamic stray current effects.

Keywords: simulation, dynamic stray current, fluctuating potentials, sacrificial anode

Procedia PDF Downloads 300

Authors: Shahzad Yousaf, Imran Shafi

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This paper presents a new method for calculation of pressure loss coefficients by use of the artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for purpose of training the network. Efficacy of the network is demonstrated by comparison of the experimental and ANN based calculated data of pressure loss coefficients for combining flows in a tee junction. Reynolds numbers ranging from 200 to 14000 and discharge ratios varying from minimum to maximum flow for calculation of pressure loss coefficients have been used. Pressure loss coefficients calculated using ANN are compared to the models from literature used in junction flows. The results achieved after the application of ANN agrees reasonably to the experimental values.

Keywords: artificial neural networks, combining flow, pressure loss coefficients, solar collector tee junctions

Procedia PDF Downloads 388

Authors: Sameer Jung Karki, Gokhan Saygili

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The allowable bearing capacity of foundation systems is determined by applying a factor of safety to the ultimate bearing capacity. Conventional ultimate bearing capacity calculations routines are based on deterministic input parameters where the nonuniformity and inhomogeneity of soil and site properties are not accounted for. Hence, the laws of mathematics like probability calculus and statistical analysis cannot be directly applied to foundation engineering. It’s assumed that the Factor of Safety, typically as high as 3.0, incorporates the uncertainty of the input parameters. This factor of safety is estimated based on subjective judgement rather than objective facts. It is an ambiguous term. Hence, a probabilistic analysis of the bearing capacity of an isolated footing on a clayey soil is carried out by using the Monte Carlo Simulation method. This simulated model was compared with the traditional discrete model. It was found out that the bearing capacity of soil was found higher for the simulated model compared with the discrete model. This was verified by doing the sensitivity analysis. As the number of simulations was increased, there was a significant % increase of the bearing capacity compared with discrete bearing capacity. The bearing capacity values obtained by simulation was found to follow a normal distribution. While using the traditional value of Factor of safety 3, the allowable bearing capacity had lower probability (0.03717) of occurring in the field compared to a higher probability (0.15866), while using the simulation derived factor of safety of 1.5. This means the traditional factor of safety is giving us bearing capacity that is less likely occurring/available in the field. This shows the subjective nature of factor of safety, and hence probability method is suggested to address the variability of the input parameters in bearing capacity equations.

Keywords: bearing capacity, factor of safety, isolated footing, montecarlo simulation

Procedia PDF Downloads 185

Authors: Malgorzata Schwab, Ashis Kumer Biswas

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In this concept paper, we explore the topic of Reversibility in Neural Networks leveraged for Network Integrity Verification and crafted the term ''Trusted Neural Network'' (TNN), paired with the API abstraction around it, to embrace the idea formally. This newly proposed high-level generalizable TNN model builds upon the Invertible Neural Network architecture, trained simultaneously in both forward and reverse directions. This allows for the original system inputs to be compared with the ones reconstructed from the outputs in the reversed flow to assess the integrity of the end-to-end inference flow. The outcome of that assessment is captured as an Integrity Score. Concrete implementation reflecting the needs of specific problem domains can be derived from this general approach and is demonstrated in the experiments. The model aspires to become a useful practice in drafting high-level systems architectures which incorporate AI capabilities.

Keywords: trusted, neural, invertible, API

Procedia PDF Downloads 145

Authors: Rafida M. Elobaid

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Most of the literature on goodness-of-fit test try to provide a theoretical basis for studying empirical distribution functions. Such goodness-of-fit tests are Kolmogorove-Simirnov and Crumer-Von Mises Type tests. However, it is likely that most of literature has not focused in details on the relationship of the values of the test statistics and skewness or kurtosis. The aim of this study is to investigate the behavior of the values of the χ2 test statistic with the variation of the skewness of right skewed distribution. A simulation study is conducted to generate random numbers from Weibull distribution. For a fixed sample sizes, different levels of skewness are considered, and the corresponding values of the χ2 test statistic are calculated. Using different sample sizes, the results show an inverse relationship between the value of χ2 test and the level of skewness for Wiebull distribution, i.e the value of χ2 test statistic decreases as the value of skewness increases. The research results also show that with large values of skewness we are more confident that the data follows the assumed distribution. Nonparametric Kendall τ test is used to confirm these results.

Keywords: goodness-of-fit test, chi-square test, simulation, continuous right skewed distributions

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Authors: Safee Chaudhary, Mahnoor Naseer Gondal, Hira Anees Awan, Abdul Rehman, Ammar Arif, Risham Hussain, Huma Khawar, Zainab Arshad, Muhammad Faizyab Ali Chaudhary, Waleed Ahmed, Muhammad Umer Sultan, Bibi Amina, Salaar Khan, Muhammad Moaz Ahmad, Osama Shiraz Shah, Hadia Hameed, Muhammad Farooq Ahmad Butt, Muhammad Ahmad, Sameer Ahmed, Fayyaz Ahmed, Omer Ishaq, Waqar Nabi, Wim Vanderbauwhede, Bilal Wajid, Huma Shehwana, Muhammad Tariq, Amir Faisal

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Cancer is a manifestation of multifactorial deregulations in biomolecular pathways. These deregulations arise from the complex multi-scale interplay between cellular and extracellular factors. Such multifactorial aberrations at gene, protein, and extracellular scales need to be investigated systematically towards decoding the underlying mechanisms and orchestrating therapeutic interventions for patient treatment. In this work, we propose ‘TISON’, a next-generation web-based multiscale modeling platform for clinical systems oncology. TISON’s unique modeling abstraction allows a seamless coupling of information from biomolecular networks, cell decision circuits, extra-cellular environments, and tissue geometries. The platform can undertake multiscale sensitivity analysis towards in silico biomarker identification and drug evaluation on cellular phenotypes in user-defined tissue geometries. Furthermore, integration of cancer expression databases such as The Cancer Genome Atlas (TCGA) and Human Proteome Atlas (HPA) facilitates in the development of personalized therapeutics. TISON is the next-evolution of multiscale cancer modeling and simulation platforms and provides a ‘zero-code’ model development, simulation, and analysis environment for application in clinical settings.

Keywords: systems oncology, cancer systems biology, cancer therapeutics, personalized therapeutics, cancer modelling

Procedia PDF Downloads 221

Authors: Mohammadreza Saviz, Sina Najafian

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This paper presents an analytical study of vibration moving elevator and shows the elevator 2D dynamic model to evaluate the vertical and lateral motion. Most elevators applied to tall buildings include compensating ropes to satisfy the balanced rope tension between the car and the counterweight. The elasticity of these ropes and springs of sets that connect cabin to ropes make the elevator car to vibrate. A two-dimensional model is derived to calculate vibrations and displacements. The simulation results were validated by the results of similar works.

Keywords: elevator, vibration, simulation, analytical solution, 2D modeling

Procedia PDF Downloads 302

Authors: Ahmadur Rahman, Showkat Ahmad Lone, Ariful Islam

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In this article, we have estimated the parameters for the failure times of units based on the sampling technique adaptive type-I progressive hybrid censoring under the step-stress partially accelerated life tests for competing risk. The failure times of the units are assumed to follow an exponential distribution. Maximum likelihood estimation technique is used to estimate the unknown parameters of the distribution and tampered coefficient. Confidence interval also obtained for the parameters. A simulation study is performed by using Monte Carlo Simulation method to check the authenticity of the model and its assumptions.

Keywords: adaptive type-I hybrid progressive censoring, competing risks, exponential distribution, simulation, step-stress partially accelerated life tests

Procedia PDF Downloads 342

Authors: A. M. Tahsini, S. Tadayon Mousavi

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The purpose of this paper is to elucidate the flow unsteady behavior for moving plug in convergent-divergent variable thrust nozzle. Compressible axisymmetric Navier-Stokes equations are used to study this physical phenomenon. Different velocities are set for plug to investigate the effect of plug movement on flow unsteadiness. Variation of mass flow rate and thrust are compared under two conditions: First, the plug is placed at different positions and flow is simulated to reach the steady state (quasi steady simulation) and second, the plug is moved with assigned velocity and flow simulation is coupled with plug movement (unsteady simulation). If plug speed is high enough and its movement time scale is at the same order of the flow time scale, variation of the mass flow rate and thrust level versus plug position demonstrate a vital discrepancy under the quasi steady and unsteady conditions. This phenomenon should be considered especially from response time viewpoints in thrusters design.

Keywords: nozzle, numerical study, unsteady, variable thrust

Procedia PDF Downloads 348

Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

Procedia PDF Downloads 126

Authors: Rabia Khaliala, Adi Vitman-Schorr

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Background: The increase in longevity of people on one hand, and on the other hand the fact that the social networks in later life become increasingly narrower, highlight the importance of Internet use to enhance quality of life (QoL). However, whether Internet use increases or decreases social networks, loneliness and quality of life is not clear-cut. Purposes: To explore the direct and/or indirect effects of Internet use on QoL, and to examine whether ethnicity and time the elderly spent with family moderate the mediation effect of Internet use on quality of life throughout loneliness. Methods: This descriptive-correlational study was carried out in 2016 by structured interviews with a convenience sample of 502 respondents aged 50 and older, living in northern Israel. Bootstrapping with resampling strategies was used for testing mediation a model. Results: Use of the Internet was found to be positively associated with QoL. However, this relationship was mediated by loneliness, and moderated by the time the elderly spent with family members. In addition, respondents' ethnicity significantly moderated the mediation effect between Internet use and loneliness. Conclusions: Internet use can enhance QoL of older adults directly or indirectly by reducing loneliness. However, these effects are conditional on other variables. The indirect effect moderated by ethnicity, and the direct effect moderated by the time the elderly spend with their families. Researchers and practitioners should be aware of these interactions which can impact loneliness and quality of life of older persons differently.

Keywords: internet use, loneliness, quality of life, social contacts

Procedia PDF Downloads 185

Authors: Saud Hassan

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This paper shows simulation for the prediction of the flow around the backlight angle of the passenger vehicle. The CFD simulations are carried out on different car models. The Ahmed model “bluff body” used as the stander model to study aerodynamics of the backlight angle. This paper described the airflow over the different car models with different backlight angles and also on the Ahmed model to determine the trailing vortices with the varying backlight angle of a passenger vehicle body. The CFD simulation is carried out with the Ahmed body which has simplified car model mainly used in automotive industry to investigate the flow over the car body surface. The main goal of the simulation is to study the behavior of trailing vortices of these models. In this paper the air flow over the slant angle of 0,5o, 12.5o, 20o, 30o, 40o are considered. As investigating on the rear backlight angle two dimensional flows occurred at the rear slant, on the other hand when the slant angle is 30o the flow become three dimensional. Above this angle sudden drop occurred in drag.

Keywords: aerodynamics, Ahemd vehicle , backlight angle, finite element method

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Authors: D. Visuwan, B. Phruksaphanrat

Abstract:

In this research, computer simulation is used for Electronic Manufacturing Service (EMS) plant layout analysis. The current layout of this manufacturing plant is a process layout, which is not suitable due to the nature of an EMS that has high-volume and high-variety environment. Moreover, quick response and high flexibility are also needed. Then, cellular manufacturing layout design was determined for the selected group of products. Systematic layout planning (SLP) was used to analyse and design the possible cellular layouts for the factory. The cellular layout was selected based on the main criteria of the plant. Computer simulation was used to analyse and compare the performance of the proposed cellular layout and the current layout. It is found that the proposed cellular layout can generate better performances than the current layout. In this research, computer simulation is used for Electronic Manufacturing Service (EMS) plant layout analysis. The current layout of this manufacturing plant is a process layout, which is not suitable due to the nature of an EMS that has high-volume and high-variety environment. Moreover, quick response and high flexibility are also needed. Then, cellular manufacturing layout design was determined for the selected group of products. Systematic layout planning (SLP) was used to analyse and design the possible cellular layouts for the factory. The cellular layout was selected based on the main criteria of the plant. Computer simulation was used to analyse and compare the performance of the proposed cellular layout and the current layout. It found that the proposed cellular layout can generate better performances than the current layout.

Keywords: layout, electronic manufacturing service plant, computer simulation, cellular manufacturing system

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Authors: Emily Kambalame

Abstract:

Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions outperformed other retention allocations by identifying the optimal solution with the fewest function evaluation

Keywords: design optimization, multi-objective evolutionary, penalty-free, water distribution systems

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Authors: H. Alheeh, M. Alameri, A. Al Tarabsheh

Abstract:

There has been a growing interest in CMOS-based sensors technology in cameras as they afford low-power, small-size, and cost-effective imaging systems. This article describes the CMOS image sensor pixel categories and presents the design and the simulation of the 3-Transistor (3T) Active Pixel Sensor (APS) in MATLAB/Simulink tool. The analysis investigates the conversion of the light into an electrical signal for a single pixel sensing circuit, which consists of a photodiode and three NMOS transistors. The paper also proposes three modes for the pixel operation; reset, integration, and readout modes. The simulations of the electrical signals for each of the studied modes of operation show how the output electrical signals are correlated to the input light intensities. The charging/discharging speed for the photodiodes is also investigated. The output voltage for different light intensities, including in dark case, is calculated and showed its inverse proportionality with the light intensity.

Keywords: APS, CMOS image sensor, light intensities photodiode, simulation

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