Search results for: computational domain

Authors: Sam Rasoulzadeh, Atefeh Mousavi

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Fluidized bed reactors are known as highly exothermic and endothermic according to uniformity in temperature as a safe and effective mean for catalytic reactors. In these reactors, a wide range of catalyst particles can be used and by using a continuous operation proceed to produce in succession. Providing optimal conditions for the operation of these types of reactors will prevent the exorbitant costs necessary to carry out laboratory work. In this regard, a hydrodynamic analysis was carried out with heat transfer in the solid-gas fluidized bed reactor for solar thermal applications. The results showed that in the fluid flow the input of the reactor has a lower temperature than the outlet, and when the fluid is passing from the reactor, the heat transfer happens between cylinder and solar panel and fluid. It increases the fluid temperature in the outlet pump and also the kinetic energy of the fluid has been raised in the outlet areas.

Keywords: heat transfer, solar reactor, fluidized bed reactor, CFD, computational fluid dynamics

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Authors: Ali Kadir, O. Anwar Beg

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Thermal barrier coatings are among the most popular methods for providing corrosion protection in high temperature applications including aircraft engine systems, external spacecraft structures, rocket chambers etc. Many different materials are available for such coatings, of which ceramics generally perform the best. Motivated by these applications, the current investigation presents detailed finite element simulations of coating stress analysis for a 3- dimensional, 3-layered model of a test sample representing a typical gas turbine component scenario. Structural steel is selected for the main inner layer, Titanium (Ti) alloy for the middle layer and Silicon Carbide (SiC) for the outermost layer. The model dimensions are 20 mm (width), 10 mm (height) and three 1mm deep layers. ANSYS software is employed to conduct three types of analysis- static structural, thermal stress analysis and also computational fluid dynamic erosion/corrosion analysis (via ANSYS FLUENT). The specified geometry which corresponds to corrosion test samples exactly is discretized using a body-sizing meshing approach, comprising mainly of tetrahedron cells. Refinements were concentrated at the connection points between the layers to shift the focus towards the static effects dissipated between them. A detailed grid independence study is conducted to confirm the accuracy of the selected mesh densities. To recreate gas turbine scenarios; in the stress analysis simulations, static loading and thermal environment conditions of up to 1000 N and 1000 degrees Kelvin are imposed. The default solver was used to set the controls for the simulation with the fixed support being set as one side of the model while subjecting the opposite side to a tabular force of 500 and 1000 Newtons. Equivalent elastic strain, total deformation, equivalent stress and strain energy were computed for all cases. Each analysis was duplicated twice to remove one of the layers each time, to allow testing of the static and thermal effects with each of the coatings. ANSYS FLUENT simulation was conducted to study the effect of corrosion on the model under similar thermal conditions. The momentum and energy equations were solved and the viscous heating option was applied to represent improved thermal physics of heat transfer between the layers of the structures. A Discrete Phase Model (DPM) in ANSYS FLUENT was employed which allows for the injection of continuous uniform air particles onto the model, thereby enabling an option for calculating the corrosion factor caused by hot air injection (particles prescribed 5 m/s velocity and 1273.15 K). Extensive visualization of results is provided. The simulations reveal interesting features associated with coating response to realistic gas turbine loading conditions including significantly different stress concentrations with different coatings.

Keywords: thermal coating, corrosion, ANSYS FEA, CFD

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Authors: A. Arjomand Kermani, N. Charbgoo, M. Alalhesabi

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In the situation of great acceleration of changes and the need for new developments in the cities on one hand and conservation and regeneration approaches on the other hand, place identity and its relation with heritage context have taken on new importance. This relation is generally mutual and complex one. The significant point in this relation is that the process of identifying something as heritage rather than just historical  phenomena, brings that which may be inherited into the realm of identity. In planning and urban design as well as environmental psychology and phenomenology domain, place identity and its attributes and components were studied and discussed. However, the relation between physical environment (especially heritage) and identity has been neglected in the planning literature. This article aims to review the knowledge on this field and develop a model on the influence and relation of these two major concepts (heritage and identity). To build this conceptual model, we draw on available literature in environmental psychology as well as planning on place identity and heritage environment using a descriptive-analytical methodology to understand how they can inform the planning strategies and governance policies. A cross-disciplinary analysis is essential to understand the nature of place identity and heritage context and develop a more holistic model of their relationship in order to be employed in planning process and decision making. Moreover, this broader and more holistic perspective would enable both social scientists and planners to learn from one another’s expertise for a fuller understanding of community dynamics. The result indicates that a combination of these perspectives can provide a richer understanding—not only of how planning impacts our experience of place, but also how place identity can impact community planning and development.

Keywords: heritage, inter-disciplinary study, place identity, planning

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Authors: Save Kumwenda, Khumbo Kalulu, Kondwani Chidziwisano, Limbani Kalumbi, Vincent Doyle, Bagrey Ngwira

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Introduction: The Malawi Government in partnership with Non-Governmental Organizations adopted Community Led Total Sanitation (CLTS) in 2008 as an approach in sanitation and hygiene promotion with an aim of declaring Malawi Open Defeacation Free (ODF) by 2015. While there is a significant body of research into CLTS available in public domain, there is little research done on challenges faced in implementing CLTS in Malawi. Methods: A cross-sectional qualitative study was carried out in three districts of Ntcheu, Balaka, and Phalombe. Data was collected using Focus Group Discussions (FGDs) and Key informant interviews (KII) and analysed manually. Results: In total, 96 people took part in FGDs and 9 people in KII. It was shown that choice of leaders after triggering was commonly done by chiefs, facilitators, and VHC without following CLTS principles as opposed to identifying individuals who showed leadership skills. Despite capacity building initiatives involving District Coordinating Teams, lack of resources to undertake follow-ups contributed to failure to sustain ODF in the community. It was also found that while most respondents appreciating the need for no subsidies, the elderly and those with disabilities felt the need for external support because do not have money for buying strong logs, slabs for durable toilet floor and also to hire people to build latrines for them. Conclusion: Effective implementation of CLTS requires comprehensive consideration of various issues that may affect its success.

Keywords: open defecation, community-led, sanitation, faecal matter, hygiene, Malawi

Procedia PDF Downloads 381

Authors: Prasanna Haddela

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Document analysis is a well matured yet still active research field, partly as a result of the intricate nature of building computational tools but also due to the inherent problems arising from the variety and complexity of human languages. Breaking down language barriers is vital in enabling access to a number of recent technologies. This paper investigates the application of document classification methods to new Sinhalese datasets. This language is geographically isolated and rich with many of its own unique features. We will examine the interpretability of the classification models with a particular focus on the use of evolved Lucene search queries generated using a Genetic Algorithm (GA) as a method of document classification. We will compare the accuracy and interpretability of these search queries with other popular classifiers. The results are promising and are roughly in line with previous work on English language datasets.

Keywords: evolved search queries, Sinhala document classification, Lucene Sinhala analyzer, interpretable text classification, genetic algorithm

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Authors: Michael Zimba

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A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency sub-band of the DWT of the suspicious image thereby leaving valuable information in the other three sub-bands, the proposed algorithm simultaneously extracts features from all the four sub-bands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates.

Keywords: affine transformation, discrete wavelet transform, radix sort, SATS

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Authors: Wan-Hsin Hsieh, Chieh-Fu Chang, Ming-Seng Kao

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In this paper, a novel method termed the Phase Coherence Acquisition (PCA) is proposed for pseudo-random (PN) sequence acquisition. By employing complex phasors, the PCA requires only complex additions in the order of N, the length of the sequence, whereas the conventional method utilizing fast Fourier transform (FFT) requires complex multiplications and additions both in the order of Nlog2N . In order to combat noise, the input and local sequences are partitioned and mapped into complex phasors in PCA. The phase differences between pairs of input and local phasors are utilized for acquisition, and thus complex multiplications are avoided. For more noise-robustness capability, the multi-layer PCA is developed to extract the code phase step by step. The significant reduction of computational loads makes the PCA an attractive method, especially when the sequence length of is extremely large which becomes intractable for the FFT-based acquisition.

Keywords: FFT, PCA, PN sequence, convolution theory

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Authors: B. S. Harish, M. B. Revanasiddappa

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Due to rapid growth of text documents in digital form, automated text classification has become an important research in the last two decades. The major challenge of text document representations are high dimension, sparsity, volume and semantics. Since the terms are only features that can be found in documents, selection of good terms (features) plays an very important role. In text classification, feature selection is a strategy that can be used to improve classification effectiveness, computational efficiency and accuracy. In this paper, we present a quantitative analysis of most widely used feature selection (FS) methods, viz. Term Frequency-Inverse Document Frequency (tf
idf ), Mutual Information (MI), Information Gain (IG), CHISquare (x2), Term Frequency-Relevance Frequency (tf
rf ), Term Strength (TS), Ambiguity Measure (AM) and Symbolic Feature Selection (SFS) to classify text documents. We evaluated all the feature selection methods on standard datasets like 20 Newsgroups, 4 University dataset and Reuters-21578.

Keywords: classifiers, feature selection, text classification

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Authors: Henrique C. C. Andrade, Ana Beatriz C. G. Silva, Fernando Luiz B. Ribeiro, Samir Maghous, Jose Claudio F. Telles, Eduardo M. R. Fairbairn

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The present paper aims at developing a parallel computational model for numerical simulation of poromechanics analyses of heterogeneous reservoirs. In the context of macroscopic poroelastoplasticity, the hydromechanical coupling between the skeleton deformation and the fluid pressure is addressed by means of two constitutive equations. The first state equation relates the stress to skeleton strain and pore pressure, while the second state equation relates the Lagrangian porosity change to skeleton volume strain and pore pressure. A specific algorithm for local plastic integration using a tangent operator is devised. A modified Cam-clay type yield surface with associated plastic flow rule is adopted to account for both contractive and dilative behavior.

Keywords: finite element method, poromechanics, poroplasticity, reservoir analysis

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Authors: Yousuf Nasser Al Khamisi

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Purpose: This paper presents a Knowledge Transfer (KT) Framework in healthcare sectors by applying a systematic literature review process to the healthcare organizations domain to identify enablers and barriers of KT in Healthcare. Methods: The paper conducted a systematic literature search of peer-reviewed papers that described key elements of KT using four databases (Medline, Cinahl, Scopus, and Proquest) for a 10-year period (1/1/2008–16/10/2017). The results of the literature review were used to build a conceptual framework of KT in healthcare organizations. The author used a systematic review of the literature, as described by Barbara Kitchenham in Procedures for Performing Systematic Reviews. Findings: The paper highlighted the impacts of using Knowledge Management (KM) concept at a healthcare organization in controlling infectious diseases in hospitals, improving family medicine performance and enhancing quality improvement practices. Moreover, it found that good-coding performance is analytically linked with a knowledge sharing network structure rich in brokerage and hierarchy rather than in density. The unavailability or ignored of the latest evidence on more cost-effective or more efficient delivery approaches leads to increase the healthcare costs and may lead to unintended results. Originality: Search procedure produced 12,093 results, of which 3523 were general articles about KM and KT. The titles and abstracts of these articles had been screened to segregate what is related and what is not. 94 articles identified by the researchers for full-text assessment. The total number of eligible articles after removing un-related articles was 22 articles.

Keywords: healthcare organisation, knowledge management, knowledge transfer, KT framework

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 157

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

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Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration

Procedia PDF Downloads 216

Authors: Sinead Impey, Damon Berry, Selma Furtado, Miriam Galvin, Loretto Grogan, Orla Hardiman, Lucy Hederman, Mark Heverin, Vincent Wade, Linda Douris, Declan O'Sullivan, Gaye Stephens

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Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: healthcare, knowledge acquisition, maximal data sets, action design science

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Authors: Vittorio Caffi, Maria Pignataro, Antonio Cosimo Devito, Marco Pesenti

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This paper deals with the integration of advanced digital design and modelling tools and methodologies, known as Building Information Modelling, into the traditional Academy educational programs for building engineers and architects. Nowadays, the challenge the Academy has to face is to present the new tools and their features to the pupils, making sure they acquire the proper skills in order to leverage the potential they offer also for the other courses embedded in the educational curriculum. The syllabus here presented refers to the “Drawing for building engineering”, “2D and 3D laboratory” and “3D modelling” curricula of the MSc in Building Engineering of the Politecnico di Milano. Such topics, included since the first year in the MSc program, are fundamental to give the students the instruments to master the complexity of an architectural or building engineering project with digital tools, so as to represent it in its various forms.

Keywords: BIM, BIM curricula, computational design, digital modelling

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Authors: Alin Veronika, Yusuf Latief

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This critical review meticulously delineates and elucidates the considerable deficiencies and voids that exist within the extant body of literature concerning the development strategies associated with risk-based Project Management Offices (PMOs). Although the advantages and positive outcomes linked to the establishment and functioning of PMOs are regularly articulated and acknowledged in various academic discourses, the empirical evidence that supports these claims frequently demonstrates a significant shortfall in methodological rigor and often encounters challenges when attempting to distinctly isolate and delineate the unique contributions and impacts of PMOs in contrast to other multifaceted organizational factors that may also play a role. This comprehensive review systematically scrutinizes and evaluates the current research landscape pertaining to the critical success factors that include, but are not limited to, strategic alignment, organizational structure, human capital, operational efficiency, technology, and the overarching influence of organizational culture, thereby identifying notable limitations within this research domain and proposing targeted areas for further scholarly investigation. Furthermore, the analysis accentuates the imperative need for the development and implementation of more sophisticated, nuanced risk assessment and mitigation frameworks that are specifically designed to cater to the unique operational characteristics of PMOs while simultaneously advocating for an elevated focus on the profound influence exerted by organizational culture and its various subcultures on the overall effectiveness and success of PMOs.

Keywords: organizational culture, project management office, risk management, risk-based PMO development

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Authors: Md. Jahoor Alam

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Recent studies suggest that Glucose controls several lifesaving pathways. Glucose molecule is reported to be responsible for the production of ROS (reactive oxygen species). In the present work, a p53-MDM2-Glucose model is developed in order to study spatiotemporal properties of the p53 pathway. The systematic model is mathematically described. The model is numerically simulated using high computational facility. It is observed that the variation in glucose concentration level triggers the system at different states, namely, oscillation death (stabilized), sustain and damped oscillations which correspond to various cellular states. The transition of these states induced by glucose is phase transition-like behaviour. Further, the amplitude of p53 dynamics with the variation of glucose concentration level follows power law behaviour, As(k) ~ kϒ, where, ϒ is a constant. Further Stochastic approach is needed for understanding of realistic behaviour of the model. The present model predicts the variation of p53 states under the influence of glucose molecule which is also supported by experimental facts reported by various research articles.

Keywords: oscillation, temporal behavior, p53, glucose

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Authors: Juliette Harper, Yu Yang

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Biofuels have gained significant attention recently due to the new regulations and agreements regarding fossil fuels and greenhouse gases being made by countries around the globe. One of the most common types of biofuels is biodiesel, primarily made via the transesterification reaction. We model this nonlinear process in MATLAB using the standard kinetic equations. Then, a nonlinear Model predictive control (NMPC) was developed to regulate this process due to its capability to handle process constraints. The feeding flow uncertainty and kinetic disturbances are further incorporated in the model to capture the real-world operating conditions. The simulation results will show that the proposed NMPC can guarantee the final composition of fatty acid methyl esters (FAME) above the target threshold with a high chance by adjusting the process temperature and flowrate. This research will allow further understanding of NMPC under uncertainties and how to design the computational strategy for larger process with more variables.

Keywords: NMPC, biodiesel, uncertainties, nonlinear, MATLAB

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Authors: Sarita Puri, Tapan K. Chaudhuri

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Chaperonin GroEL is a tetradecameric Escherichia coli protein having identical subunits of 57 kDa. The elucidation of thermodynamic parameters related to stability for the native GroEL is not feasible as it undergoes irreversible unfolding because of its large size (800kDa) and multimeric nature. Nevertheless, it is important to determine the thermodynamic stability parameters for the highly stable GroEL protein as it helps in folding and holding of many substrate proteins during many cellular stresses. Properly folded monomers work as building-block for the formation of native tetradecameric GroEL. Spontaneous refolding behavior of monomeric GroEL makes it suitable for protein-denaturant interactions and thermodynamic stability based studies. The urea mediated unfolding is a three state process which means there is the formation of one intermediate state along with native and unfolded states. The heat mediated denaturation is a two-state process. The unfolding process is reversible as observed by the spontaneous refolding of denatured protein in both urea and head mediated refolding processes. Analysis of folding/unfolding data provides a measure of various thermodynamic stability parameters for the monomeric GroEL. The proposed mechanism of unfolding of monomeric GroEL is a three state process which involves formation of one stable intermediate having folded apical domain and unfolded equatorial, intermediate domains. Research in progress is to demonstrate the importance of specific residues in stability and oligomerization of GroEL protein. Several mutant versions of GroEL are under investigation to resolve the above mentioned issue.

Keywords: equilibrium unfolding, monomeric GroEl, spontaneous refolding, thermodynamic stability

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Authors: Mehmet Bozca

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Singular value decomposition based optimisation of geometric design parameters of a 5-speed gearbox is studied. During the optimisation, a four-degree-of freedom torsional vibration model of the pinion gear-wheel gear system is obtained and the minimum singular value of the transfer matrix is considered as the objective functions. The computational cost of the associated singular value problems is quite low for the objective function, because it is only necessary to compute the largest and smallest singular values (µmax and µmin) that can be achieved by using selective eigenvalue solvers; the other singular values are not needed. The design parameters are optimised under several constraints that include bending stress, contact stress and constant distance between gear centres. Thus, by optimising the geometric parameters of the gearbox such as, the module, number of teeth and face width it is possible to obtain a light-weight-gearbox structure. It is concluded that the all optimised geometric design parameters also satisfy all constraints.

Keywords: Singular value, optimisation, gearbox, torsional vibration

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Authors: Felicia Segeth, Florian G. Klein, Lea Berger, Andreas Kolk, Per S. Holm

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The entry of oncolytic viruses (OVs) into clinical application opens groundbreaking changes in current and future treatment regimens. However, despite their potent anti-cancer activity in vitro, clinical studies revealed limitations of OVs as monotherapy. The same applies to CDK 4/6 inhibitors (CDK4/6i) targeting cell cycle as well as bromodomain and extra-terminal domain inhibitors (BETi) targeting gene expression. In this study, the anti-tumoral effect of XVir-N-31, an YB-1 dependent oncolytic adenovirus, was evaluated in combination with Ribociclib, a CDK4/6i, and JQ1, a BETi. The head and neck squamous cell carcinoma (HNSCC) cell lines Fadu, SAS, and Cal-33 were used. DNA replication and gene expression of XVir-N-31 was measured by RT-qPCR, protein expression by western blotting, and cell lysis by SRB assays. Treatment with CDK4/6i and BETi increased viral gene expression, viral DNA replication, and viral particle formation. The data show that the combination of oncolytic adenovirus XVir-N-31 with CDK4/6i & BETi acts highly synergistic in cancer cell lysis. Furthermore, additional molecular analyses on this subject demonstrate that the positive transcription elongation factor P-TEFb plays a decisive role in this regard, indicating an influence of the combinational therapy on gene transcription control. The combination of CDK4/6i & BETi and XVir-N-31 is an attractive strategy to achieve substantial cancer cell killing and is highly suitable for clinical testing.

Keywords: adenovirus, BET, CDK4/6, HNSCC, P-TEFb, YB-1

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Authors: Paola Comella, Vincenzo Francani, Paola Gattinoni

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This paper presents the Colzate-Vertova landslide, a Deep Seated Gravitational Slope Deformation (DSGSD) located in the Seriana Valley, Northern Italy. The paper aims at describing the development as well as evaluating the factors that influence the evolution of the landslide. After defining the conceptual model of the landslide, numerical simulations were developed using a finite element numerical model, first with a two-dimensional domain, and later with a three-dimensional one. The results of the 2-D model showed a displacement field typical of a sackung, as a consequence of the erosion along the Seriana Valley. The analysis also showed that the groundwater flow could locally affect the slope stability, bringing about a reduction in the safety factor, but without reaching failure conditions. The sensitivity analysis carried out on the strength parameters pointed out that slope failures could be reached only for relevant reduction of the geotechnical characteristics. Such a result does not fit the real conditions observed on site, where a number of small failures often develop all along the hillslope. The 3-D model gave a more comprehensive analysis of the evolution of the DSGSD, also considering the border effects. The results showed that the convex profile of the slope favors the development of displacements along the lateral valley, with a relevant reduction in the safety factor, justifying the existing landslides.

Keywords: deep seated gravitational slope deformation, Italy, landslide, numerical modeling

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Authors: Yang-Kuei Lin, Yun-Xi Zhang

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This research focuses on the bicriteria correlated parallel machine scheduling problem. The two objective functions considered in this problem are to minimize maximum lateness and total weighted completion time. We first present a mixed integer programming (MIP) model that can find the entire efficient frontier for the studied problem. Next, we have proposed a bicriteria heuristic that can find non-dominated solutions for the studied problem. The performance of the proposed bicriteria heuristic is compared with the efficient frontier generated by solving the MIP model. Computational results indicate that the proposed bicriteria heuristic can solve the problem efficiently and find a set of diverse solutions that are uniformly distributed along the efficient frontier.

Keywords: bicriteria, correlated parallel machines, heuristic, scheduling

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Authors: Viliam Makis, Farnoosh Naderkhani, Leila Jafari

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In this paper, we present a model and an algorithm for the calculation of the optimal control limit, average cost, sample size, and the sampling interval for an optimal Bayesian chart to control the proportion of defective items produced using a semi-Markov decision process approach. Traditional p-chart has been widely used for controlling the proportion of defectives in various kinds of production processes for many years. It is well known that traditional non-Bayesian charts are not optimal, but very few optimal Bayesian control charts have been developed in the literature, mostly considering finite horizon. The objective of this paper is to develop a fast computational algorithm to obtain the optimal parameters of a Bayesian p-chart. The decision problem is formulated in the partially observable framework and the developed algorithm is illustrated by a numerical example.

Keywords: Bayesian control chart, semi-Markov decision process, quality control, partially observable process

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Authors: Marasovic Branka, Aljinovic Zdravka, Poklepovic Tea

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Numerical methods like binomial and trinomial trees and finite difference methods can be used to price a wide range of options contracts for which there are no known analytical solutions. American options are the most famous of that kind of options. Besides numerical methods, American options can be valued with the approximation formulas, like Bjerksund-Stensland formulas from 1993 and 2002. When the value of American option is approximated by Bjerksund-Stensland formulas, the computer time spent to carry out that calculation is very short. The computer time spent using numerical methods can vary from less than one second to several minutes or even hours. However to be able to conduct a comparative analysis of numerical methods and Bjerksund-Stensland formulas, we will limit computer calculation time of numerical method to less than one second. Therefore, we ask the question: Which method will be most accurate at nearly the same computer calculation time?

Keywords: Bjerksund and Stensland approximations, computational analysis, finance, options pricing, numerical methods

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Authors: Jean-Philippe Gagnon, Benjamin Saute, Stéphane Boubanga-Tombet

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Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. However, it is well known that most combustion gases such as carbon dioxide (CO₂), water vapor (H₂O), and carbon monoxide (CO) selectively absorb/emit infrared radiation at discrete energies, i.e., over a very narrow spectral range. Therefore, temperature profiles of most combustion processes derived from conventional broadband imaging are inaccurate without prior knowledge or assumptions about the spectral emissivity properties of the combustion gases. Using spectral filters allows estimating these critical emissivity parameters in addition to providing selectivity regarding the chemical nature of the combustion gases. However, due to the turbulent nature of most flames, it is crucial that such information be obtained without sacrificing temporal resolution. For this reason, Telops has developed a time-resolved multispectral imaging system which combines a high-performance broadband camera synchronized with a rotating spectral filter wheel. In order to illustrate the benefits of using this system to characterize combustion experiments, measurements were carried out using a Telops MS-IR MW on a very simple combustion system: a wood fire. The temperature profiles calculated using the spectral information from the different channels were compared with corresponding temperature profiles obtained with conventional broadband imaging. The results illustrate the benefits of the Telops MS-IR cameras for the characterization of laminar and turbulent combustion systems at a high temporal resolution.

Keywords: infrared, multispectral, fire, broadband, gas temperature, IR camera

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Authors: Tiago Sampaio, André Vasconcelos, Bruno Fragoso

Abstract:

The Normalized Systems Theory, which is designed to be applied to software architectures, provides a set of theorems, elements and rules, with the purpose of enabling evolution in Information Systems, as well as ensuring that they are ready for change. In order to make that possible, this work’s solution is to apply the Normalized Systems Theory to the domain of enterprise architectures, using Archimate. This application is achieved through the adaptation of the elements of this theory, making them artifacts of the modeling language. The theorems are applied through the identification of the viewpoints to be used in the architectures, as well as the transformation of the theory’s encapsulation rules into architectural rules. This way, it is possible to create normalized enterprise architectures, thus fulfilling the needs and requirements of the business. This solution was demonstrated using the Portuguese Public Procurement System. The Portuguese government aims to make this system as fair as possible, allowing every organization to have the same business opportunities. The aim is for every economic operator to have access to all public tenders, which are published in any of the 6 existing platforms, independently of where they are registered. In order to make this possible, we applied our solution to the construction of two different architectures, which are able of fulfilling the requirements of the Portuguese government. One of those architectures, TO-BE A, has a Message Broker that performs the communication between the platforms. The other, TO-BE B, represents the scenario in which the platforms communicate with each other directly. Apart from these 2 architectures, we also represent the AS-IS architecture that demonstrates the current behavior of the Public Procurement Systems. Our evaluation is based on a comparison between the AS-IS and the TO-BE architectures, regarding the fulfillment of the rules and theorems of the Normalized Systems Theory and some quality metrics.

Keywords: archimate, architecture, broker, enterprise, evolvable systems, interoperability, normalized architectures, normalized systems, normalized systems theory, platforms

Procedia PDF Downloads 358

Authors: M. Fozan Ur Rab, Mahrukh, M. Alam, N. Sheikh

Abstract:

The purpose of this study is to analyze various high lift low Reynolds number airfoils using two-dimensional Computational Fluid Dynamics (CFD) code in the isolated flow field and select optimum airfoil to suit the motorsports application. The airfoil is selected after comparing the stall behavior, transition location, pressure recovery, pressure distribution and boundary layer characteristics of various airfoils. The prime consideration while selecting airfoil is highest Cl while achieving the sustainable performance over a range of Reynolds numbers encountered on the race track. The increase in Cl is always accompanied by the increase in Cd but this must be compromised since the main goal is to increase an aerodynamic grip. It is always desirable to increase the down-force in Formula One (F1)/Formula Student (FS) to gain reduction in lap time. This paper establishes the criteria for selection of high lift low Reynolds number airfoil while considering various parameters which affect the performance of airfoils.

Keywords: aerodynamics, airfoil, downforce, formula student, lap time

Procedia PDF Downloads 288

Authors: Zhifei Hu, Feng Xia

Abstract:

In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.

Keywords: graph attention network, knowledge graph, recommendation, information propagation

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Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

Abstract:

A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

Procedia PDF Downloads 156