Search results for: CFD (Computational Fluid Dynamics)

Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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Authors: Sinchan Ghosh, Fahad Al Basir, Santanu Ray, Sabyasachi Bhattacharya

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The cooperatively breeding birds have two major ranks for the sexually mature birds. The breeders mate and produce offspring while the non-breeding helpers increase the chick production rate through help in mate-finding and allo-parenting. However, the chicks also cooperate to raise their younger siblings through warming, defending and food sharing. Although, the existing literatures describes the evolution of allo-parenting in birds but do not differentiate the significance of allo-parenting in sexually immature and mature helpers separately. This study addresses the significance of both immature and mature helpers’ contribution to the total sustainable bird population in a breeding site using Blue-tailed bee-eater as a test-bed species. To serve this purpose, a mathematical model has been built considering each social status and chicks as separate but interactive compartments. Also, to observe the dynamics of each social status with changing prey abundance, a prey population has been introduced as an additional compartment. The model was analyzed for stability condition and was validated using field-data. A simulation experiment was then performed to observe the change in equilibria with a varying helping rate from both the helpers. The result from the simulation experiment suggest that the cooperative breeding population changes its population sizes significantly with a change in helping rate from the sexually immature helpers. On the other hand, the mature helpers do not contribute to the stability of the population equilibrium as much as the immature helpers.

Keywords: Blue-tailed bee eater, Altruism, Mathematical Ethology, Behavioural modelling

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Authors: Vineeta Kaushik, Manisha Goel

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Chaperones are proteins that help other proteins fold correctly, and are found in all domains of life i.e., prokaryotes, eukaryotes and archaea. Various comparative genomic studies have suggested that the archaeal protein folding machinery appears to be highly similar to that found in eukaryotes. In case of protein folding; slow rotation of peptide prolyl-imide bond is often the rate limiting step. Formation of the prolyl-imide bond during the folding of a protein requires the assistance of other proteins, termed as peptide prolyl cis-trans isomerases (PPIases). Cyclophilins constitute the class of peptide prolyl isomerases with a wide range of biological function like protein folding, signaling and chaperoning. Most of the cyclophilins exhibit PPIase enzymatic activity and play active role in substrate protein folding which classifies them as a category of molecular chaperones. Till date, there is not very much data available in the literature on archaeal cyclophilins. We aim to compare the structural and biochemical features of the cyclophilin protein from within the three domains to elucidate the features affecting their stability and enzyme activity. In the present study, we carry out in-silico analysis of the cyclophilin proteins to predict their conserved residues, sites under positive selection and compare these proteins to their bacterial and eukaryotic counterparts to predict functional divergence. We also aim to clone and express these proteins in heterologous system and study their biophysical characteristics in detail using techniques like CD and fluorescence spectroscopy. Overall we aim to understand the features contributing to the folding, stability and dynamics of the archaeal cyclophilin proteins.

Keywords: biophysical characterization, x-ray crystallography, chaperone-like activity, cyclophilin, PPIase activity

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Authors: Samaneh Nazemi, Ayla Bahramian, Marzieh Aghazadeh

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Saliva is a clear liquid composed of water, electrolytes, glucose, amylase, glycoproteins, and antimicrobial enzymes. The presence of a wide range of molecules and proteins in saliva has made this fluid valuable in screening for some diseases as well as epidemiological studies. Saliva is easier than serum to collect in large populations. Due to the importance of sodium and glucose levels in many biological processes, this study investigates the relationship between sodium and glucose levels in salivary and serum samples of healthy individuals referring to Tabriz Dental School. This descriptive-analytical study was performed on 40 healthy individuals referred to the Oral Diseases Department of Tabriz Dental School. Serum and saliva samples were taken from these patients according to standard protocols. Data were presented as mean (standard deviation) and frequency (percentage) for quantitative and qualitative variables. Pearson test, paired-samples T-test and SPSS 24 software were used to determine the correlation between serum and salivary levels of these biomarkers. In this study, P less than 0.05% is considered significant. Out of 40 participants in this study, 14 (35%) were male, and 26 (65%) were female. According to the results of this study, the mean salivary sodium (127.53 ml/dl) was lower than the mean serum sodium (141.2725 ml/dl). In contrast, the mean salivary glucose (4.55 ml/dl) was lower than the mean serum glucose (89.7575 ml/dl). The result of paired samples T-test (p-value<0.05) showed that there is a statistically significant difference between the mean of serum sodium and salivary sodium, as well as between the serum glucose and salivary glucose. Pearson correlation test results showed that there is no significant correlation between serum sodium and salivary sodium (p-value >0.05), but here is a positive correlation between serum glucose and salivary glucose (p-value<0.001). Both serum sodium and glucose were higher than salivary sodium and glucose.In conclusion, this study found that there was not a statistical relationship between salivary glucose and serum glucose and also salivary sodium and serum sodium of healthy individuals. Perhaps salivary samples can’t be used to measure glucose and sodium in these individuals.

Keywords: glucose, saliva, serum, sodium

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Authors: Babatunde James Falaye, Shi Hai Dong, Kayode John Oyewumi

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We study the effects of oblateness up to J4 of the primaries and power-law density profile (PDP) on the linear stability of libration location of an innitesimal mass within the framework of restricted three body problem (R3BP), by using a more realistic model in which a disc with PDP is rotating around the common center of the system mass with perturbed mean motion. The existence and stability of triangular equilibrium points have been explored. It has been shown that triangular equilibrium points are stable for 0 < μ < μc and unstable for μc ≤ μ ≤ 1/2, where c denotes the critical mass parameter. We find that, the oblateness up to J2 of the primaries and the radiation reduces the stability range while the oblateness up to J4 of the primaries increases the size of stability both in the context where PDP is considered and ignored. The PDP has an eect of about ≈0:01 reduction on the application of c to Earth-Moon and Jupiter-Moons systems. We find that the comprehensive effects of the perturbations have a stabilizing proclivity. However, the oblateness up to J2 of the primaries and the radiation of the primaries have tendency for instability, while coecients up to J4 of the primaries have stability predisposition. In the limiting case c = 0, and also by setting appropriate parameter(s) to zero, our results are in excellent agreement with the ones obtained previously. Libration points play a very important role in space mission and as a consequence, our results have a practical application in space dynamics and related areas. The model may be applied to study the navigation and station-keeping operations of spacecraft (innitesimal mass) around the Jupiter (more massive) -Callisto (less massive) system, where PDP accounts for the circumsolar ring of asteroidal dust, which has a cloud of dust permanently in its wake.

Keywords: libration points, oblateness, power-law density profile, restricted three-body problem

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Authors: E. R. Swart, S. J. Gismondi, N. R. Swart, C. E. Bell

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We present an heuristic algorithm that decides graph non-Hamiltonicity. All graphs are directed, each undirected edge regarded as a pair of counter directed arcs. Each of the n! Hamilton cycles in a complete graph on n+1 vertices is mapped to an n-permutation matrix P where p(u,i)=1 if and only if the ith arc in a cycle enters vertex u, starting and ending at vertex n+1. We first create exclusion set E by noting all arcs (u, v) not in G, sufficient to code precisely all cycles excluded from G i.e. cycles not in G use at least one arc not in G. Members are pairs of components of P, {p(u,i),p(v,i+1)}, i=1, n-1. A doubly stochastic-like relaxed LP formulation of the Hamilton cycle decision problem is constructed. Each {p(u,i),p(v,i+1)} in E is coded as variable q(u,i,v,i+1)=0 i.e. shrinks the feasible region. We then implement the Weak Closure Algorithm (WCA) that tests necessary conditions of a matching, together with Boolean closure to decide 0/1 variable assignments. Each {p(u,i),p(v,j)} not in E is tested for membership in E, and if possible, added to E (q(u,i,v,j)=0) to iteratively maximize |E|. If the WCA constructs E to be maximal, the set of all {p(u,i),p(v,j)}, then G is decided non-Hamiltonian. Only non-Hamiltonian G share this maximal property. Ten non-Hamiltonian graphs (10 through 104 vertices) and 2000 randomized 31 vertex non-Hamiltonian graphs are tested and correctly decided non-Hamiltonian. For Hamiltonian G, the complement of E covers a matching, perhaps useful in searching for cycles. We also present an example where the WCA fails.

Keywords: Hamilton cycle decision problem, computational complexity theory, graph theory, theoretical computer science

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: S. M. Abdul Khader, Anurag Ayachit, Raghuvir Pai, K. A. Ahmed, V. R. K Rao, S. Ganesh Kamath

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The numerical simulation has made tremendous advances in investigating the blood flow phenomenon through elastic arteries. Such study can be useful in demonstrating the disease progression and haemodynamics of cardiovascular diseases such as atherosclerosis. In the present study, patient specific case diagnosed with partially stenosed complete right ICA and normal left carotid bifurcation without any atherosclerotic plaque formation is considered. 3D patient specific carotid bifurcation model is generated based on CT scan data using MIMICS-4.0 and numerical analysis is performed using FSI solver in ANSYS-14.5. The blood flow is assumed to be incompressible, homogenous and Newtonian, while the artery wall is assumed to be linearly elastic. The two-way sequentially-coupled transient FSI analysis is performed using FSI solver for three pulse cycles. The haemodynamic parameters such as flow pattern, Wall Shear Stress, pressure contours and arterial wall deformation are studied at the bifurcation and critical zones such as stenosis. The variation in flow behavior is studied throughout the pulse cycle. Also, the simulation results reveals that there is a considerable increase in the flow behavior in stenosed carotid in contrast to the normal carotid bifurcation system. The investigation also demonstrates the disturbed flow pattern especially at the bifurcation and stenosed zone elevating the haemodynamics, particularly during peak systole and later part of the pulse cycle. The results obtained agree well with the clinical observation and demonstrates the potential of patient specific numerical studies in prognosis of disease progression and plaque rupture.

Keywords: fluid-structure interaction, arterial stenosis, wall shear stress, carotid artery bifurcation

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Authors: M. Insiat Islam Rabby, M. Mahbubur Rahman, Eshanul Islam, A. K. M. Sadrul Islam

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The numerical and simulative analysis of laminar heat exchange convection of aluminum oxide (Al₂O₃) - water nanofluid for the developed region through two parallel plates is presented in this present work. The second order single phase energy equation, mass and momentum equation are solved by using finite volume method with the ANSYS FLUENT 16 software. The distance between two parallel plates is 4 mm and length is 600 mm. Aluminum oxide (Al₂O₃) is used as nanoparticle and water is used as the base/working fluid for the investigation. At the time of simulation 1% to 5% volume concentrations of the Al₂O₃ nanoparticles are used for mixing with water to produce nanofluid and a wide range of interval of Reynolds number from 500 to 1100 at constant heat flux 500 W/m² at the channel wall has also been introduced. The result reveals that for increasing the Reynolds number the Nusselt number and heat transfer coefficient are increased linearly and friction factor decreased linearly in the developed region for both water and Al₂O₃-H₂O nanofluid. By increasing the volume fraction of Al₂O₃-H₂O nanofluid from 1% to 5% the value of Nusselt number increased rapidly from 0.7 to 7.32%, heat transfer coefficient increased 7.14% to 31.5% and friction factor increased very little from 0.1% to 4% for constant Reynolds number compared to pure water. At constant heat transfer coefficient 700 W/m2-K the pumping power advantages have been achieved 20% for 1% volume concentration and 62% for 3% volume concentration of nanofluid compared to pure water.

Keywords: convective heat transfer, pumping power, constant heat flux, nanofluid, nanoparticles, volume concentration, thermal conductivity

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Authors: P. Comendador, I. Garcia, S. Orozco, L. Santamaria, M. Amutio, G. Lopez, M. Olazar

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In situ CO₂ capture in steam reforming processes has been studied in the last years as an alternative for increasing H₂ yields and H₂ purity in the product stream. For capturing the CO₂ at the reforming conditions, CaO-based sorbents are usually employed due to their properties at high temperature, low cost and high availability. However, the challenge is to develop high-capacity (gCO₂/gsorbent) materials that retain their capacity over cycles of operation. Besides, since the objective is to capture the CO₂ generated in situ, another key aspect is the sorption dynamics, which means that, in order to efficiently use the sorbent, it has to capture the CO₂ at a rate equal to or higher than the generation rate. In this work, different CaO-based materials have been prepared to aim at meeting these criteria. First, and by using the wet mixing method, different inert materials (Mg, Ce and Al) were combined with CaO. Second, and with the inert material selected (Mg), the effect of its concentration in the final material was studied. Transversally, the calcination temperature was also evaluated. It was determined that the wet mixing method is a simple procedure suitable for the preparation of CaO sorbents mixed with inert materials. The materials prepared by mixing the CaO with Mg have shown satisfactory anti-sintering properties and adequate sorption kinetics for their application in steam reforming processes. Regarding the concentration of Mg in the solid, it was concluded that high values contribute to the stability but at the expense of losing sorption capacity. Finally, it was observed that high calcination temperatures negatively affected the sorption properties of the final materials due to the decrease in the pore volume and the specific surface area.

Keywords: calcination temperature effect, CO₂ capture, Mg-Ce-Al stabilizers, Mg varying concentration effect, Sorbent stabilization

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Authors: Angelis P. Barlampas

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Theoretical background Disorders of fixation and rotation of the large intestine, result in the existence of its parts in ectopic anatomical positions. In case of symptomatology, the clinical picture is complicated by the possible symptomatology of the neighboring anatomical structures and a differential diagnostic problem arises. Target The purpose of this work is to demonstrate the difficulty of revealing the real cause of abdominal pain, in cases of anatomical variants and the decisive contribution of imaging and especially that of computed tomography. Methods A patient came to the emergency room, because of acute pain in the right hypochondrium. Clinical examination revealed tenderness in the gallbladder area and a positive Murphy's sign. An ultrasound exam depicted a normal gallbladder and the patient was referred for a CT scan. Results Flexible, unfixed ascending colon and cecum, located in the anatomical region of the right mesentery. Opacities of the surrounding peritoneal fat and a small linear concentration of fluid can be seen. There was an appendix of normal anteroposterior diameter with the presence of air in its lumen and without clear signs of inflammation. There was an impression of possible inflammatory swelling at the base of the appendix, (DD phenomenon of partial volume; e.t.c.). Linear opacities of the peritoneal fat in the region of the second loop of the duodenum. Multiple diverticula throughout the colon. Differential Diagnosis The differential diagnosis includes the following: Inflammation of the base of the appendix, diverticulitis of the cecum-ascending colon, a rare case of second duodenal loop ulcer, tuberculosis, terminal ileitis, pancreatitis, torsion of unfixed cecum-ascending colon, embolism or thrombosis of a vascular intestinal branch. Final Diagnosis There is an unfixed cecum-ascending colon, which is exhibiting diverticulitis.

Keywords: unfixed cecum-ascending colon, abdominal pain, malrotation, abdominal CT, congenital anomalies

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Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

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Authors: Ekpeti Bukola Grace, Mahmoudi Sabar Esmail, Chaer Issa

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Global energy consumption has been increasing steadily over the last half - century, and this trend is projected to continue. As energy demand rises in many countries throughout the world due to population growth, natural ventilation in buildings has been identified as a viable option for lowering these demands, saving costs, and also lowering CO2 emissions. However, natural ventilation is driven by forces that are generally unpredictable in nature thus, it is important to manage the resulting airflow in order to maintain pleasant indoor conditions, making it a complex system that necessitates specific control approaches. The effective application of fuzzy logic technique amidst other intelligent systems is one of the best ways to bridge this gap, as its control dynamics relates more to human reasoning and linguistic descriptions. This article reviewed existing literature and presented practical solutions by applying fuzzy logic control with optimized techniques, selected input parameters, and expert rules to design a more effective control system. The control monitors used indoor temperature, outdoor temperature, carbon-dioxide levels, wind velocity, and rain as input variables to the system, while the output variable remains the control of window opening. This is achieved through the use of fuzzy logic control tool box in MATLAB and running simulations on SIMULINK to validate the effectiveness of the proposed system. Comparison analysis model via simulation is carried out, and with the data obtained, an improvement in control actions and energy savings was recorded.

Keywords: fuzzy logic, intelligent control systems, natural ventilation, optimization

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Authors: Laura Angulo, Petra Salamon, Martin Banse, Frederic Storkamp

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Fisheries subsidies are focus on reduce management costs or deliver income benefits to fishers. In 2015, total fishery budgetary transfers in 31 OECD countries represented 35% of their total landing value. However, subsidies to fishing have adverse effects on trade and it has been claimed that they may contribute directly to overfishing. Therefore, this paper analyses to what extend fisheries subsidies may 1) influence capture production facing quotas and 2) affect price dynamics. The study uses the fish module in AGMEMOD (Agriculture Member States Modelling, details see Chantreuil et al. (2012)) which covers eight fish categories (cephalopods; crustaceans; demersal marine fish; pelagic marine fish; molluscs excl. cephalopods; other marine finfish species; freshwater and diadromous fish) for EU member states and other selected countries developed under the SUCCESS project. This model incorporates transfer payments directly linked to fisheries operational costs. As aquaculture and wild fishery are not included within the WTO Agreement on Agriculture, data on fisheries subsidies is obtained from the OECD Fisheries Support Estimates (FSE) database, which provides statistics on budgetary transfers to the fisheries sector. Since support has been moving from budgetary transfers to General Service Support Estimate the last years, subsidies in capture production may not present substantial effects. Nevertheless, they would still show the impact across countries and fish categories within the European Union.

Keywords: AGMEMOD, budgetary transfers, EU Member States, fish model, fisheries support estimate

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Authors: Esra Yaldız, Tugba Bulbul Bahtiyar, Dicle Aydın

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Humans meet their need for shelter via housing which they structure in line with habits and necessities. In housing culture, traditional dwelling has an important role as a social and cultural transmitter. It provides concrete data by being planned in parallel with users’ life style and habits, having their own dynamics and components as well as their designs in harmony with nature, environment and the context they exist. Textures of traditional dwelling create a healthy and cozy living environment by means of adaptation to natural conditions, topography, climate, and context; utilization of construction materials found nearby and usage of traditional techniques and forms; and natural isolation of construction materials used. One of the examples of traditional settlements in Anatolia is Kilistra (Gökyurt) settlement of Konya province. Being among the important centers of Christianity in the past, besides having distinctive architecture, culture, natural features, and geographical differences (climate, geological structure, material), Kilistra can also be identified as a traditional settlement consisting of family, religious and economic structures as well as cultural interaction. The foundation of this study is the traditional residential texture of Kilistra with its unique features. The objective of this study is to assess the conformity of traditional residential texture of Kilistra with present topography, climatic data, and geographical values within the context of human scale construction, usage of green space, indigenous construction materials, construction form, building envelope, and space organization in housing.

Keywords: traditional residential architecture, Kilistra, Anatolia, Konya

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Authors: Berhanu Terfa, Nengcheng C.

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The study deals with the analysis of urban expansion and land transformation of Hawass City using remote sensing data and landscape metrics during last three decades (1987–2017). Remote sensing data from Various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used to examine the urban expansion, growth types, and spatial isolation within the urban landscape to develop an understanding the trends of built-up growth in Hawassa City, Ethiopia. Landscape metrics and built-up density were employed to analyze the pattern, process and overall growth status. The area under investigation was divided into concentric circles with a consecutive circle of 1 km incremental radius from the central pixel (Central Business District) for analysis. The result exhibited that the built-up area had increased by 541.32% between 1987 and 2017and an extension growth types (more than 67 %) was observed. The major growth took place in north-west direction followed by north direction in haphazard manner during 1987–1995 period, whereas predominant built-up development was observed in south and southwest direction during 1995–2017 period. Land scape metrics result revealed that the of urban patches density, total edge and edge density increased, while mean nearest neighbors’ distance decreased showing the tendency of sprawl.

Keywords: landscape metrics, spatial patterns, remote sensing, multi-temporal, urban sprawl

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Authors: Haoshui Yu, Donghoi Kim, Truls Gundersen

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Low-temperature waste heat is abundant in the process industries, and large amounts of Liquefied Natural Gas (LNG) cold energy are discarded without being recovered properly in LNG terminals. Power generation is an effective way to utilize low-temperature waste heat and LNG cold energy simultaneously. Organic Rankine Cycles (ORCs) and CO₂ power cycles are promising technologies to convert low-temperature waste heat and LNG cold energy into electricity. If waste heat and LNG cold energy are utilized simultaneously in one system, the performance may outperform separate systems utilizing low-temperature waste heat and LNG cold energy, respectively. Low-temperature waste heat acts as the heat source and LNG regasification acts as the heat sink in the combined system. Due to the large temperature difference between the heat source and the heat sink, cascaded power cycle configurations are proposed in this paper. Cascaded power cycles can improve the energy efficiency of the system considerably. The cycle operating at a higher temperature to recover waste heat is called top cycle and the cycle operating at a lower temperature to utilize LNG cold energy is called bottom cycle in this study. The top cycle condensation heat is used as the heat source in the bottom cycle. The top cycle can be an ORC, transcritical CO₂ (tCO₂) cycle or supercritical CO₂ (sCO₂) cycle, while the bottom cycle only can be an ORC due to the low-temperature range of the bottom cycle. However, the thermodynamic path of the tCO₂ cycle and sCO₂ cycle are different from that of an ORC. The tCO₂ cycle and the sCO₂ cycle perform better than an ORC for sensible waste heat recovery due to a better temperature match with the waste heat source. Different combinations of the tCO₂ cycle, sCO₂ cycle and ORC are compared to screen the best configurations of the cascaded power cycles. The influence of the working fluid and the operating conditions are also investigated in this study. Each configuration is modeled and optimized in Aspen HYSYS. The results show that cascaded tCO₂/ORC performs better compared with cascaded ORC/ORC and cascaded sCO₂/ORC for the case study.

Keywords: LNG cold energy, low-temperature waste heat, organic Rankine cycle, supercritical CO₂ cycle, transcritical CO₂ cycle

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Sourina Bej

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Since the process of decolonization in 1940, several countries in South Asia have witnessed intra-state conflicts owing to ineffective political governance. The conflicts have remained protracted as the countries have failed to make a holistic transition to a democratic state. Nepal is one such South Asian country facing a turmultous journey from monarchy to republicanism. The paper aims to focus on the democratic transition in the context of Nepal’s political, legal and economic institutions. The presence of autocratic feudalistic and centralised state structure with entrenched socio-economic inequalities has resulted in mass uprising only to see the country slip back to the old order. Even a violent civil war led by the Maoists could not overhaul the political relations or stabilize the democratic space. The paper aims to analyse the multiple political, institutional and operational challenges in the implementation of the peace agreement with the Maoist. Looking at the historical background, the paper will examine the problematic nation-building that lies at the heart of fragile peace process in Nepal. Regional dynamics have played a big role in convoluting the peace-building. The new constitution aimed at conflict resolution brought to the open, deep seated hatred among different ethnic groups in Nepal. Apart from studying the challenges to the peace process and the role of external players like India and China in the political reconstruction, the paper will debate on a viable federal solution to the ethnic conflict in Nepal. If the current government fails to pass a constitution accepted by most ethnic groups, Nepal will remain on the brink of new conflict outbreaks.

Keywords: democratisation, ethnic conflict, Nepal, peace process

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Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

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The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

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Authors: Theddeus Tochukwu Akano, Omotayo Abayomi Fakinlede

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Proper understanding of the behavior of compliant mechanisms use by athletes is important in order to avoid catastrophic failure. Such compliant mechanisms like the flex-run require the knowledge of their dynamic response and deformation behavior under quickly varying loads. The modeling of finite deformations of the compliant athletic system is described by Neo-Hookean model under contact-impact conditions. The dynamic impact-contact governing equations for both the target and impactor are derived based on the updated Lagrangian approach. A method where contactor and target are considered as a united body is applied in the formulation of the principle of virtual work for the bodies. In this paper, methods of continuum mechanics and nonlinear finite element method were deployed to develop a model that could capture the behavior of the compliant athletic system under quickly varying loads. A hybrid system of symbolic algebra (AceGEN) and a compiled back end (AceFEM) were employed, leveraging both ease of use and computational efficiency. The simulated results reveal the effect of the various contact-impact conditions on the deformation behavior of the impacting compliant mechanism.

Keywords: eigenvalue problems, finite element method, robin boundary condition, sturm-liouville problem

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Authors: Mona Hejazi, Ali Motie Nasrabadi

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Epilepsy is a persistent neurological disorder that affects more than 50 million people worldwide. Hence, there is a necessity to introduce an efficient prediction model for making a correct diagnosis of the epileptic seizure and accurate prediction of its type. In this study we consider how the Effective Connectivity (EC) patterns obtained from intracranial Electroencephalographic (EEG) recordings reveal information about the dynamics of the epileptic brain and can be used to predict imminent seizures, as this will enable the patients (and caregivers) to take appropriate precautions. We use this definition because we believe that effective connectivity near seizures begin to change, so we can predict seizures according to this feature. Results are reported on the standard Freiburg EEG dataset which contains data from 21 patients suffering from medically intractable focal epilepsy. Six channels of EEG from each patients are considered and effective connectivity using Directed Transfer Function (DTF) and Granger Causality (GC) methods is estimated. We concentrate on effective connectivity standard deviation over time and feature changes in five brain frequency sub-bands (Alpha, Beta, Theta, Delta, and Gamma) are compared. The performance obtained for the proposed scheme in predicting seizures is: average prediction time is 50 minutes before seizure onset, the maximum sensitivity is approximate ~80% and the false positive rate is 0.33 FP/h. DTF method is more acceptable to predict epileptic seizures and generally we can observe that the greater results are in gamma and beta sub-bands. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

Keywords: effective connectivity, Granger causality, directed transfer function, epilepsy seizure prediction, EEG

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Authors: M. Rahou, A. J. Andrews, G. Rosengarten

Abstract:

One of the main challenges in high-temperature solar thermal applications transfer concentrated solar radiation to the load with minimum energy loss and maximum overall efficiency. The use of a solar concentrator in conjunction with bundled optical fibres has potential advantages in terms of transmission energy efficiency, technical feasibility and cost-effectiveness compared to a conventional heat transfer system employing heat exchangers and a heat transfer fluid. In this paper, a theoretical and computer simulation method is described to estimate the net solar radiation transmission from a solar concentrator into and through optical fibres to a thermal application at the end of the fibres over distances of up to 100 m. A key input to the simulation is the angular distribution of radiation intensity at each point across the aperture plane of the optical fibre. This distribution depends on the optical properties of the solar concentrator, in this case, a parabolic mirror with a small secondary mirror with a common focal point and a point-focus Fresnel lens to give a collimated beam that pass into the optical fibre bundle. Since solar radiation comprises a broad band of wavelengths with very limited spatial coherence over the full range of spectrum only ray tracing models absorption within the fibre and reflections at the interface between core and cladding is employed, assuming no interference between rays. The intensity of the radiation across the exit plane of the fibre is found by integrating across all directions and wavelengths. Results of applying the simulation model to a parabolic concentrator and point-focus Fresnel lens with typical optical fibre bundle will be reported, to show how the energy transmission varies with the length of fibre.

Keywords: concentrated radiation, fibre bundle, parabolic dish, fresnel lens, transmission

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

Abstract:

The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Claudia Ehrentraut, Osama Ibrahim, Hercules Dalianis

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Policy making situations are real-world problems that exhibit complexity in that they are composed of many interrelated problems and issues. To be effective, policies must holistically address the complexity of the situation rather than propose solutions to single problems. Formulating and understanding the situation and its complex dynamics, therefore, is a key to finding holistic solutions. Analysis of text based information on the policy problem, using Natural Language Processing (NLP) and Text analysis techniques, can support modelling of public policy problem situations in a more objective way based on domain experts knowledge and scientific evidence. The objective behind this study is to support modelling of public policy problem situations, using text analysis of verbal descriptions of the problem. We propose a formal methodology for analysis of qualitative data from multiple information sources on a policy problem to construct a causal diagram of the problem. The analysis process aims at identifying key variables, linking them by cause-effect relationships and mapping that structure into a graphical representation that is adequate for designing action alternatives, i.e., policy options. This study describes the outline of an algorithm used to automate the initial step of a larger methodological approach, which is so far done manually. In this initial step, inferences about key variables and their interrelationships are extracted from textual data to support a better problem structuring. A small prototype for this step is also presented.

Keywords: public policy, problem structuring, qualitative analysis, natural language processing, algorithm, inference extraction

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Authors: Einav Srulovici, Michal Grinstein-Weiss, George Knafl, Linda Beeber, Shawn Kneipp, Barbara Mark

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Background: The asset-building theoretical framework (ABTF) is acknowledged as the most complete framework thus far for depicting the relationships between asset accumulation (the stock of a household’s saved resources available for future investment) and health outcomes. Although the ABTF takes into consideration the reciprocal relationship between asset accumulation and health, no ABTF based study has yet examined this relationship. Therefore, the purpose of this study was to test the ABTF and psychological distress, focusing on the reciprocal relationship between assets accumulation and psychological distress. Methods: The study employed longitudinal data from 6,295 families from the 2001 and 2007 Panel Study of Income Dynamics data sets. Structural equation modeling (SEM) was used to test the reciprocal relationship between asset accumulation and psychological distress. Results: In general, the data displayed a good fit to the model. The longitudinal SEM found that asset accumulation significantly increased with a decreased in psychological distress over time, while psychological distress significantly increased with an increase in asset accumulation over time, confirming the existence of the hypothesized reciprocal relationship. Conclusions: Individuals who are less psychological distressed might have more energy to engage in activities, such as furthering their education or obtaining better jobs that are in turn associated with greater asset accumulation, while those who have greater assets may invest those assets in riskier investments, resulting in increased psychological distress. The confirmation of this reciprocal relationship highlights the importance of conducting longitudinal studies and testing the reciprocal relationship between asset accumulation and other health outcomes.

Keywords: asset-building theoretical framework, psychological distress, structural equation modeling, reciprocal relationship

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Authors: H. Troudi, M. Ghiss, Z. Tourki, M. Ellejmi

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Packed columns of liquefied petroleum gas (LPG) consists of separating the liquid mixture of propane and butane to pure gas components by the distillation phenomenon. The flow of the gas and liquid inside the columns is operated by two ways: The co-current and the counter current operation. Heat, mass and species transfer between phases represent the most important factors that influence the choice between those two operations. In this paper, both processes are discussed using computational CFD simulation through ANSYS-Fluent software. Only 3D half section of the packed column was considered with one packed bed. The packed bed was characterized in our case as a porous media. The simulations were carried out at transient state conditions. A multi-component gas and liquid mixture were used out in the two processes. We utilized the Euler-Lagrange approach in which the gas was treated as a continuum phase and the liquid as a group of dispersed particles. The heat and the mass transfer process was modeled using multi-component droplet evaporation approach. The results show that the counter-current process performs better than the co-current, although such limitations of our approach are noted. This comparison gives accurate results for computations times higher than 2 s, at different gas velocity and at packed bed porosity of 0.9.

Keywords: co-current, counter-current, Euler-Lagrange model, heat transfer, mass transfer

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Authors: Chu Liu

Abstract:

With the development of society and the changes of the times, the requirements for the cultivation of learners are different. In the 21st century, STEM education has become a boom in the development of education in various countries, aiming to improve the comprehensive ability of learners in science, technology, engineering, and mathematics. The rise of robot education provides an effective way for STEM education to cultivate computational thinking ability, interdisciplinary ability, problem-solving ability, and teamwork ability. Although robot education has been developed in China for several years, it still lacks a standard curriculum system. This article uses programming software as a platform, through the research and analysis of 'Basic Education Information Technology Curriculum Standards (2012 Edition)', combines with the actual learning situation of learners, tries to conduct teaching project design research, and aims at providing references for the teaching ideas and method of robot education courses. In contemporary society, technological advances increasingly require creativity. Innovative comprehensive talents urgently need a radical and effective education reform to keep up with social changes. So in this context, robot teaching design can be used for students. The tendency of creativity to influence is worth to be verified.

Keywords: STEM education, robot teaching, primary and secondary school students, tendency of creativity

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Authors: T. A. Rosy, M. R. I. Talukdar, N. S. Juyena, F. Y. Bari, M. N. Islam

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The ovarian follicular dynamics, vaginal electrical resistance (VER) and progesterone (P4) and estrogen (E2) profiles were investigated during estrus cycle in four indigenous ewes. Daily VER values were recorded with heat detector. The follicles were observed and measured by trans-rectal ultrasonography. Blood was collected daily for hormonal profiles. Results showed a significant variation in VER values (P<0.05) at estrus in regards to ewes and cycles. The day difference between two successive lower values in VER waves ranged from 13-17 days which might indicate the estrus cycle in indigenous ewes. Trans-rectal ultrasonography of ovaries revealed the presence of two to four waves of follicular growth during the study period. Results also showed that follicular diameter was negatively correlated with VER values. Study of hormonal profiles by ELISA revealed a positive correlation between E2 concentration and development of follicle and negative correlation between P4 concentration and development of follicle. The concentrations of estradiol increased at the time of estrus and then fall down in a basal level. Development of follicular size was accompanied by an increase in the concentration of serum estradiol. Inversely, when follicles heed to ovulation concentration of progesterone starts to fall down and after ovulation it turns its way to the zenith and remains at this state until next ovulatory follicle comes to its maximum diameter. This study could help scientists to set up a manipulative reproductive technique for improving genetic values of sheep in Bangladesh.

Keywords: ovarian follicle, hormonal profile, sheep, ultrasonography, vaginal electrical resistance

Procedia PDF Downloads 253