Search results for: computational domain

Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in pipe bends caused by particles is a major obstacle in the oil and gas fields and might cause the breakdown of production equipment. This work studied the effects imposed by flow velocity and impact of solid particles diameter in an elbow; erosion rate was verified with experimental data using the computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model was employed to calculate the air/solid particle flow in an elbow. One erosion model and three-particle rebound models were used to predict the erosion rate on the 90° elbows. The generic erosion model was used in the CFD-based erosion model, and after comparing it with experimental data, results showed agreement with the CFD-based predictions as observed.

Keywords: erosion, prediction, elbow, computational fluid dynamics

Procedia PDF Downloads 157

Authors: Mounir Kehal

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The post-globalization epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behavior has come to provide the competitive and comparative edge. Enterprises have turned to explicit - and even conceptualizing on tacit - knowledge management to elaborate a systematic approach to develop and sustain the intellectual capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualized. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper, we present an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: Kalpana Dahiya

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This paper discusses a two-level hierarchical time minimization transportation problem, which is an important class of transportation problems arising in industries. This problem has been studied by various researchers, and a number of polynomial time iterative algorithms are available to find its solution. All the existing algorithms, though efficient, have some shortcomings. The current study proposes an alternate solution algorithm for the problem that is more efficient in terms of computational time than the existing algorithms. The results justifying the underlying theory of the proposed algorithm are given. Further, a detailed comparison of the computational behaviour of all the algorithms for randomly generated instances of this problem of different sizes validates the efficiency of the proposed algorithm.

Keywords: global optimization, hierarchical optimization, transportation problem, concave minimization

Procedia PDF Downloads 161

Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: wavelet transform, computational error, computational duration, strong ground motion data

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Authors: Malo Pocheau-Lesteven, Olivier Le Maître

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Engineering and optimisation of complex systems is often achieved through multi-disciplinary analysis of the system, where each subsystem is modeled and interacts with other subsystems to model the complete system. The coherence of the output of the different sub-systems is achieved through the use of compatibility constraints, which enforce the coupling between the different subsystems. Due to the complexity of some sub-systems and the computational cost of evaluating their respective models, it is often necessary to build surrogate models of these subsystems to allow repeated evaluation these subsystems at a relatively low computational cost. In this paper, gaussian processes are used, as their probabilistic nature is leveraged to evaluate the likelihood of satisfying the compatibility constraints. This paper presents infilling strategies to build accurate surrogate models of the subsystems in areas where they are likely to meet the compatibility constraint. It is shown that these infilling strategies can reduce the computational cost of building surrogate models for a given level of accuracy. An application of these methods to velocity prediction programs used in offshore racing naval architecture further demonstrates these method's applicability in a real engineering context. Also, some examples of the application of uncertainty quantification to field of naval architecture are presented.

Keywords: infilling strategy, gaussian process, multi disciplinary analysis, velocity prediction program

Procedia PDF Downloads 157

Authors: Matthew J. Flynn

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In early 2022, a thirty-mile column of Russian armor and assault vehicles sat poised to move south on the road to Kiev. That force has withdrawn as the Russians concentrate on attacking eastern Ukraine. Vladimir Putin’s armies appear content to destroy cities in an effort to attrit the Ukrainian will to continue fighting. That pivot signifies the acceptance of the ascendancy of the defense that now dictates any battlefield world-wide. To defeat what military theorist Carl von Clausewitz labeled “the stronger form of war” with a successful offensive requires an exercise in future war. In the past, the ascendancy of the defense has been overcome by a number of things including the application of superior leadership, better technology, organizational adaptation, and surpassing environmental limitations. A look at how each of these factors came to impact battle can tell us a great deal about what Ukraine means to tomorrow’s fight, and where the focus should lie to win the next war. Civilians presently secure the defensive ascendancy impacting warfare by dominating the shifts from domain to domain thanks to controlling access to cyberspace. That mandate will be tested and eventually falter. This paper tests the desirability of that proposition, as well as hoping for something more from humanity other than repeated and frequent wars making future war look much like past wars. As nations struggle to control cyberspace, a referendum on war as part of the human condition comes into focus.

Keywords: cyber, domains, future war, Putin, Ukraine

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Authors: Martin Hewing, Katharina Hölzle

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Organizations increasingly use environmental stimuli and ideas from users within participatory innovation processes in order to tap new sources of knowledge. The research presented in this article focuses on users who shape the distant edges of markets and currently are not using products and services from a domain– so called potential users. Those users at the peripheries are perceived to contribute more novel information, by which they better reflect shifts in needs and behavior than current users in the core market. Their contributions in collaborative and creative problem-solving processes and how they generate ideas for discontinuous innovations are of particular interest. With an experimental design, we compare ideas from potential and current users and analyze the effects of cognitive distance in collaboration and the utilization of explicit and tacit knowledge. We find potential users to generate more original ideas, particularly when they collaborate with someone experienced within the domain. Their ideas are most obviously characterized by an increased level of surprise and unusualness compared to dominant designs, which is rooted in contexts and does not require technological leaps. Collaboration with potential users can therefore result in new ways to leverage technological competences. Furthermore, the cross-fertilization arising from cognitive distance between a potential and a current user is asymmetric due to differences in the nature of their utilized knowledge and personal objectives. This paper discusses implications for innovation research and the management of early innovation processes.

Keywords: user collaboration, co-creation, discontinuous innovation, innovation research

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Authors: Mahendra Singh, Narasimhareddy Ravuru

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For the past decade, the production of biodiesel has significantly increased along with its by-product, glycerol. Biodiesel-derived glycerol massive entry into the glycerol market has caused its value to plummet. Newer ways to utilize the glycerol by-product must be implemented or the biodiesel industry will face serious economic problems. The biodiesel industry should consider steam reforming glycerol to produce hydrogen gas. Steam reforming is the most efficient way of producing hydrogen and there is a lot of demand for it in the petroleum and chemical industries. This study investigates the feasibility of glycerol steam reforming in an industrial sized fixed bed reactor. In this paper, using computational fluid dynamic (CFD) simulations, the extent of the transport resistances that would occur in an industrial sized reactor can be visualized. An important parameter in reactor design is the size of the catalyst particle. The size of the catalyst cannot be too large where transport resistances are too high, but also not too small where an extraordinary amount of pressure drop occurs. The goal of this paper is to find the best catalyst size under various flow rates that will result in the highest conversion. Computational fluid dynamics simulated the transport resistances and a pseudo-homogenous reactor model was used to evaluate the pressure drop and conversion. CFD simulations showed that glycerol steam reforming has strong internal diffusion resistances resulting in extremely low effectiveness factors. In the pseudo-homogenous reactor model, the highest conversion obtained with a Reynolds number of 100 (29.5 kg/h) was 9.14% using a 1/6 inch catalyst diameter. Due to the low effectiveness factors and high carbon deposition rates, a fluidized bed is recommended as the appropriate reactor to carry out glycerol steam reforming.

Keywords: computational fluid dynamic, fixed bed reactor, glycerol, steam reforming, biodiesel

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Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Kunto Wibowo Agung Prodjonoto

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Occasionally, opportunities occur not due to chances but threats. This, however, is often not realized because a greater threat is perceived to be anything that threatens, endangers, or harms, resulting in bad impacts that are also part of the risk and consequence. As a result, more focus tends to direct towards the bad impacts. Risk, in this case, shall be seen rather as something challenging, which can turn to be an opportunity to tackle an obstacle. Therefore, it does not seem exaggerating if later, risk can be considered as a challenge that presents an opportunity. So as in the context of the threat of natural disasters which gives an idea that opportunities exist. Nature referred to in a fashion as 'natural disasters' captured an expression to picture the 'threats' aspect, which instructively implying a chance of opportunity. This is quite logical, as SWOT (strengths, weaknesses, opportunities, threats) analysis can evaluate the situation at hand related to the analysis of various factors in formulating strategies to deal with natural disaster situations. The analytical method created by Albert Humphrey is indeed not an analytical tool to provide solutions, but certainly 'opportunities and challenges' are discussed therein on a vertical line, where opportunities are posited on the positive axis, and threats are posed on the negative axis. Observing this dynamism, the challenges and threats of disasters are having opportunity relevance to moralizing opportunities, that by quality poses universalism populist characteristics, universalism characteristics, and regional characteristics. Here, universalism appears as an opportunity domain underneath the threats and challenges of natural disasters.

Keywords: universality, opportunities, threats, challenges of natural disasters

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Authors: Alaa Koaik, Bruno Jurkiewiez, Sylvain Bel

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Recently, the use of GFRP pultruded profiles increased in the domain of civil engineering especially in the construction of sandwiched slabs and footbridges. However, under heavy loads, the risk of using these profiles increases due to their high deformability and instability as a result of their weak stiffness and orthotropic nature. A practical solution proposes the assembly of these profiles with concrete slabs to create a stiffer hybrid element to support higher loads. The connection of these two elements is established either by traditional means of steel studs (bolting in our case) or bonding technique. These two techniques have their advantages and disadvantages regarding the mechanical behavior and in-situ implementation. This paper presents experimental results of interface characterization and bending behavior of two hybrid beams, PB7 and PB8, designed and constructed using both connection techniques. The results obtained are exploited to design and build a hybrid footbridge BPBP1 which is tested within service limits (elastic domain). Analytical methods are also developed to analyze the behavior of these structures in the elastic range and the ultimate phase. Comparisons show acceptable differences mainly due to the sensitivity of the GFRP moduli as well as the non-linearity of concrete elements.

Keywords: analytical model, concrete, flexural behavior, GFRP pultruded profile, hybrid structure, interconnection slip, push-out

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Authors: Atousa Ataieyan, Salvador A. Gomez-Lopera, Gennaro Sepede

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Today, due to the growing urban population and consequently, the increasing water demand in cities, the amount of contaminants entering the water resources is increasing. This can impose harmful effects on the quality of the downstream water. Therefore, predicting the concentration of discharged pollutants at different times and distances of the interested area is of high importance in order to carry out preventative and controlling measures, as well as to avoid consuming the contaminated water. In this paper, the concentration distribution of an injected conservative pollutant in a square reservoir containing four symmetric blocks and three sources using Finite Volume Method (FVM) is simulated. For this purpose, after estimating the flow velocity, classical Advection-Diffusion Equation (ADE) has been discretized over the studying domain by Backward Time- Backward Space (BTBS) scheme. Then, the discretized equations for each node have been derived according to the initial condition, boundary conditions and point contaminant sources. Finally, taking into account the appropriate time step and space step, a computational code was set up in MATLAB. Contaminant concentration was then obtained at different times and distances. Simulation results show how using BTBS differentiating scheme and FVM as a numerical method for solving the partial differential equation of transport is an appropriate approach in the case of two-dimensional contaminant transfer in an advective-diffusive flow.

Keywords: BTBS differentiating scheme, contaminant concentration, finite volume, mass transfer, water pollution

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Authors: Indri Mahadiraka Rumamby, R. R. Dwinanti Rika Marthanty, Jessica Sjah

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Smoothed particle hydrodynamics (SPH) was originally created to simulate nonaxisymmetric phenomena in astrophysics. However, this method still has several shortcomings, namely the high computational cost required to model values with high resolution and problems with boundary conditions. The difficulty of modeling boundary conditions occurs because the SPH method is influenced by particle deficiency due to the integral of the kernel function being truncated by boundary conditions. This research aims to answer if SPH modeling with a focus on boundary layer interactions and continuous flow can produce quantifiably accurate values with low computational cost. This research will combine algorithms and coding in the main program of meandering river, continuous flow algorithm, and solid-fluid algorithm with the aim of obtaining quantitatively accurate results on solid-fluid interactions with the continuous flow on a meandering channel using the SPH method. This study uses the Fortran programming language for modeling the SPH (Smoothed Particle Hydrodynamics) numerical method; the model is conducted in the form of a U-shaped meandering open channel in 3D, where the channel walls are soil particles and uses a continuous flow with a limited number of particles.

Keywords: smoothed particle hydrodynamics, computational fluid dynamics, numerical simulation, fluid mechanics

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Authors: Swati Sharma, R. P. Sharma

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We intend to study the nonlinear evolution of the parallel propagating finite frequency Alfvén wave (also called Dispersive Alfvén wave/Hall MHD wave) propagating in the solar wind regime of the solar region when a perpendicularly propagating magnetosonic wave is present in the background. The finite frequency Alfvén wave behaves differently from the usual non-dispersive behavior of the Alfvén wave. To study the nonlinear processes (such as filamentation) taking place in the solar regions such as solar wind, the dynamical equation of both the waves are derived. Numerical simulation involving finite difference method for the time domain and pseudo spectral method for the spatial domain is then performed to analyze the transient evolution of these waves. The power spectra of the Dispersive Alfvén wave is also investigated. The power spectra shows the distribution of the magnetic field intensity of the Dispersive Alfvén wave over different wave numbers. For DAW the spectra shows a steepening for scales larger than the proton inertial length. This means that the wave energy gets transferred to the solar wind particles as the wave reaches higher wave numbers. This steepening of the power spectra can be explained on account of the finite frequency of the Alfvén wave. The obtained results are consistent with the observations made by CLUSTER spacecraft.

Keywords: solar wind, turbulence, dispersive alfven wave

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Bouabdellah Abed, Mohamed Bouzit, Lakhdar Bouarbi

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The objective of this study is to investigate numerically the effect of roof shaped on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, Pvol = 96%. A three-dimensional computational fluid dynamics (CFD) model for evaluating air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier–Stokes (RANS) equations and the k-Epsilon EARSM turbulence model as close of the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated against the wind tunnel experiment. Having established this, the wind flow and pollutant dispersion in urban street canyons of six roof shapes are simulated. The numerical simulation agrees reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated, this complexity is increased with presence of tree and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped. The results also indicated that the corners eddies provide additional ventilation and lead to lower traffic pollutant concentrations at the street canyon ends.

Keywords: street canyon, pollutant dispersion, trees, building configuration, numerical simulation, k-Epsilon EARSM

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Authors: Farhan A. Alenizi

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Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.

Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing

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Authors: K. Shaji Mon, P. R. John Sreenidhi

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In deep-submicrometer CMOS processes, time-domain resolution of a digital signal is becoming higher than voltage resolution of analog signals. This claim is nowadays pushing toward a new circuit design paradigm in which the traditional analog signal processing is expected to be progressively substituted by the processing of times in the digital domain. Within this novel paradigm, digitally controlled delay lines (DCDL) should play the role of digital-to-analog converters in traditional, analog-intensive, circuits. Digital delay locked loops are highly prevalent in integrated systems.The proposed paper addresses the glitches present in delay circuits along with area,power dissipation and signal integrity.The digitally controlled delay lines(DCDL) under study have been designed in a 90 nm CMOS technology 6 layer metal Copper Strained SiGe Low K Dielectric. Simulation and synthesis results show that the novel circuits exhibit no glitches for dual output coarse DCDL with less power dissipation and consumes less area compared to the glitch free NAND based DCDL.

Keywords: glitch free, NAND-based DCDL, CMOS, deep-submicrometer

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: activities of daily living, classification, internet of things, machine learning, prediction, smart home

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Authors: Rachel Koshy, Nazrila Hairizan Bt. Nasir, Samsiah Bt. Awang, Kamaliah Bt. Mohamad Noh

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Malaysia collaborated as a ‘trailblazer’ country with PHCPI (Primary Health Care Performance Initiative) to populate the Primary Health Care (PHC) Vital Signs Profile (VSP) for the country. The PHC VSP provides an innovative snapshot of the primary health care system's performance. Four domains were assessed: system financing, system capacity, system performance, and system equity, and completed in 2019. There were two phases using a mixed method study design. The first phase involved a quantitative study, utilising existing secondary data from national and international sources. In the case of unavailability of data for any indicators, comparable alternative indicators were used. The second phase was a mixed quantitative-qualitative approach to measure the functional capacity based on governance and leadership, population health needs, inputs, population health management, and facility organisation and management. PHC spending constituted 35% of overall health spending in Malaysia, with a per capita PHC spending of $152. The capacity domain was strong in the three subdomains of governance and leadership, information system, and funds management. The two subdomains of drugs & supplies and facility organisation & management had low scores, but the lowest score was in empanelment of the population under the population health management. The PHC system performed with an access index of 98%, quality index of 84%, and service coverage of 62%. In the equity domain, there was little fluctuation in the coverage of reproductive, maternal, newborn, and child health services by mother’s level of education and under-five child mortality between urban and rural areas. The public sector was stronger in the capacity domain as compared to the private sector. This is due to the different financing, organisational structures, and service delivery mechanism. The VSP has identified areas for improvement in the effort to provide high-quality PHC for the population. The gaps in PHC can be addressed through the system approach and the positioning of public and private primary health care delivery systems.

Keywords: primary health care, health system, system domains, vital signs profile

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Authors: Simon Caba, Raja Abou Ackl, Svend Rasmussen, Nicholas E. Pedersen

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It is a challenge to directly monitor cavitation in a pump application during operation because of a lack of visual access to validate the presence of cavitation and its form of appearance. In this work, experimental investigations are carried out in an inline single-stage centrifugal pump with optical access. Hence, it gives the opportunity to enhance the value of CFD tools and standard cavitation measurements. Experiments are conducted using two impellers running in the same volute at 3000 rpm and the same flow rate. One of the impellers used is optimized for lower NPSH₃% by its blade design, whereas the other one is manufactured using a standard casting method. The cavitation is detected by pump performance measurements, vibration measurements and high-speed image recordings. The head drop and the pump casing vibration caused by cavitation are correlated with the visual appearance of the cavitation. The vibration data is recorded in an axial direction of the impeller using accelerometers recording at a sample rate of 131 kHz. The vibration frequency domain data (up to 20 kHz) and the time domain data are analyzed as well as the root mean square values. The high-speed recordings, focusing on the impeller suction side, are taken at 10,240 fps to provide insight into the flow patterns and the cavitation behavior in the rotating impeller. The videos are synchronized with the vibration time signals by a trigger signal. A clear correlation between cloud collapses and abrupt peaks in the vibration signal can be observed. The vibration peaks clearly indicate cavitation, especially at higher NPSHA values where the hydraulic performance is not affected. It is also observed that below a certain NPSHA value, the cavitation started in the inlet bend of the pump. Above this value, cavitation occurs exclusively on the impeller blades. The impeller optimized for NPSH₃% does show a lower NPSH₃% than the standard impeller, but the head drop starts at a higher NPSHA value and is more gradual. Instabilities in the head drop curve of the optimized impeller were observed in addition to a higher vibration level. Furthermore, the cavitation clouds on the suction side appear more unsteady when using the optimized impeller. The shape and location of the cavitation are compared to 3D fluid flow simulations. The simulation results are in good agreement with the experimental investigations. In conclusion, these investigations attempt to give a more holistic view on the appearance of cavitation by comparing the head drop, vibration spectral data, vibration time signals, image recordings and simulation results. Data indicates that a criterion for cavitation detection could be derived from the vibration time-domain measurements, which requires further investigation. Usually, spectral data is used to analyze cavitation, but these investigations indicate that the time domain could be more appropriate for some applications.

Keywords: cavitation, centrifugal pump, head drop, high-speed image recordings, pump vibration

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Authors: J. Joy, T. H. New, I. H. Ibrahim

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A computational study on bio-inspired NACA634-021 hydrofoils with leading-edge protuberances has been carried out to investigate their hydrodynamic flow control characteristics at a Reynolds number of 14,000 and different angles-of-attack. The numerical simulations were performed using ANSYS FLUENT and based on Reynolds-Averaged Navier-Stokes (RANS) solver mode incorporated with k-ω Shear Stress Transport (SST) turbulence model. The results obtained indicate varying flow phenomenon along the peaks and troughs over the span of the hydrofoils. Compared to the baseline hydrofoil with no leading-edge protuberances, the leading-edge modified hydrofoils tend to reduce flow separation extents along the peak regions. In contrast, there are increased flow separations in the trough regions of the hydrofoil with leading-edge protuberances. Interestingly, it was observed that dissimilar flow separation behaviour is produced along different peak- or trough-planes along the hydrofoil span, even though the troughs or peaks are physically similar at each interval for a particular hydrofoil. Significant interactions between adjacent flow structures produced by the leading-edge protuberances have also been observed. These flow interactions are believed to be responsible for the dissimilar flow separation behaviour along physically similar peak- or trough-planes.

Keywords: computational fluid dynamics, flow separation control, hydrofoils, leading-edge protuberances

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Authors: Imane Benghalia, Mohammed Zamoum, Rachid Boucetta

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Hydrodynamic cavitation is a complex physical phenomenon that appears in hydraulic systems (pumps, turbines, valves, Venturi tubes, etc.) when the fluid pressure decreases below the saturated vapor pressure. The works carried out in this study aimed to get a better understanding of the cavitating flow phenomena. For this, we have numerically studied a cavitating bubbly flow through a Venturi nozzle. The cavitation model is selected and solved using a commercial computational fluid dynamics (CFD) code. The obtained results show the effect of the inlet pressure (10, 7, 5, and 2 bars) of the Venturi on pressure, the velocity of the fluid flow, and the vapor fraction. We found that the inlet pressure of the Venturi strongly affects the evolution of the pressure, velocity, and vapor fraction formation in the cavitating flow.

Keywords: cavitating flow, CFD, phase change, venturi

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Authors: Norhashidah Hj. Mohd Ali, Teng Wai Ping

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In this paper, we present a high order group explicit method in solving the two dimensional Helmholtz equation. The presented method is derived from a nine-point fourth order finite difference approximation formula obtained from a 45-degree rotation of the standard grid which makes it possible for the construction of iterative procedure with reduced complexity. The developed method will be compared with the existing group iterative schemes available in literature in terms of computational time, iteration counts, and computational complexity. The comparative performances of the methods will be discussed and reported.

Keywords: explicit group method, finite difference, helmholtz equation, rotated grid, standard grid

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Authors: Mounir Kehal, Adel Al Araifi

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The post-globalisation epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper we present likewise an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: Mi-Hye Hwang, Young Min Son, Kichan Lee, Bang-Hun Hyun, Byeong Yeal Jung

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Botulism is a paralytic disease of human beings and animals caused by neurotoxin produced by Clostridium botulinum. The neurotoxins are genetically distinguished into 8 types, A to H. Ingestion of performed toxin, usually types B, C, and D, have been shown to produce diseases in most cases of cattle botulism. Vaccination is the best measure to prevent cattle botulism. However, the commercially available toxoid-based vaccines are difficult and hazardous to produce. We produced recombinant protein using gene of heavy chain domain of botulinum toxin B of which binds to cellular receptor of neuron cells and used as immunogen. In this study, we evaluated the safety and efficacy of botulism vaccine composed of recombinant types B. Safety test was done by National Regulation for Veterinary Biologicals. For efficacy test, female ICR mice (5 weeks old) were subcutaneously injected, intraperitoneally challenged, and examined the survival rates compared with vaccination and non-vaccination group. Mouse survival rate of recombinant types B vaccine was above 80%, while one of non-vaccination group was 0%. A vaccine composed of recombinant types B was safe and efficacious in mouse. Our results suggest that recombinant heavy chain receptor binding domain can be used as an effective vaccine candidate for type B botulism.

Keywords: botulism, livestock, vaccine, recombinant protein, toxin

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Authors: Ashish Kumar Agrahari, Amit Kumar

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Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore the atomistic level impact of PIGA mutations on the structure and dynamics of the protein. In the current work, we are mainly interested to get insights into the molecular mechanism of PIGA mutations. In the initial step, we screened the most pathogenic mutations from the pool of publicly available mutations. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and subjected to 50ns molecular dynamics simulation. Our computational study suggests that four mutations are highly vulnerable to altering the structural conformation and stability of the PIGA protein, which illustrates its association with PNH and MCAHS2 phenotype.

Keywords: homology modeling, molecular dynamics simulation, missense mutations PNH, MCAHS2, PIGA

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Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

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The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

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Authors: Troy M. Houser

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The successor representation balances flexible and efficient reinforcement learning by learning to predict the future, given the present. As such, the successor representation models stimuli as what future states they lead to. Therefore, two stimuli that are perceptually dissimilar but lead to the same future state will come to be represented more similarly. This is very similar to an older behavioral paradigm -the acquired equivalence paradigm, which measures the generalization of learned associations. Here, we test via computational modeling the plausibility that the successor representation is the mechanism by which people generalize knowledge learned in the acquired equivalence paradigm. Computational evidence suggests that this is a plausible mechanism for acquired equivalence and thus can guide future empirical work on individual differences in associative-based generalization.

Keywords: acquired equivalence, successor representation, generalization, decision-making

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Authors: Nagaratna Rajur, J. D. Mallapur, Y. B. Kirankumar

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The security in mobile communication is very different from the internet or telecommunication, because of its poor user interface and limited processing capacity, as well as combination of complex network protocols. Hence, it poses a challenge for less memory usage and low computation speed based security system. Security involves all the activities that are undertaken to protect the value and on-going usability of assets and the integrity and continuity of operations. An effective network security strategies requires identifying threats and then choosing the most effective set of tools to combat them. Cryptography is a simple and efficient way to provide security in communication. RSA is an asymmetric key approach that is highly reliable and widely used in internet communication. However, it has not been efficiently implemented in mobile communication due its computational complexity and large memory utilization. The proposed algorithm modifies the current RSA to be useful in mobile communication by reducing its computational complexity and memory utilization.

Keywords: M-RSA, sensor networks, sensor applications, security

Procedia PDF Downloads 342