Search results for: experimental and numerical modelling

Authors: Seda Sahin, Emin Akata

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Obturator foramen is a specific structure in pelvic bone images and recognition of it is a new concept in medical image processing. Moreover, segmentation of bone structures such as obturator foramen plays an essential role for clinical research in orthopedics. In this paper, we present a novel method to analyze the similarity between the substructures of the imaged region and a hand drawn template, on hip radiographs to detect obturator foramen accurately with integrated usage of Marker-controlled Watershed segmentation and Zernike moment feature descriptor. Marker-controlled Watershed segmentation is applied to seperate obturator foramen from the background effectively. Zernike moment feature descriptor is used to provide matching between binary template image and the segmented binary image for obturator foramens for final extraction. The proposed method is tested on randomly selected 100 hip radiographs. The experimental results represent that our method is able to segment obturator foramens with % 96 accuracy.

Keywords: medical image analysis, segmentation of bone structures on hip radiographs, marker-controlled watershed segmentation, zernike moment feature descriptor

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Authors: A. J. Shah, G. R. Vesmawala

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Connections perform a fundamental role in the steel structures as global behaviour. In order to evaluate the real influence of the physical and geometrical parameters that control their behaviour, many experimental tests and analysis have been developed but a definitive answer to the problem in question still stands. Here, various configurations of bolts were tried and the resulting moment rotation (M-θ) curves were plotted. The connection configuration is such that two bolts are located above each of the flanges and beside each of the webs. The model considers the combined effects of prying action, the formation of yield lines, and failures due to punching shear and beam section failure. For many types of connections, the stiffness at the service load level falls somewhere in between the fully restrained and simple limits and designers need to account for its behaviour. The (M-θ) curves are generally assumed to be the best characterization of connection behaviour. The moment rotation curves are generally derived from experiments on cantilever type specimens. The moments are calculated directly from the statics of the specimen, while the rotations are measured over a distance typically equal to the point of loading. Thus, this paper establishes the relationship between M-θ behaviour of different types of connections tested and presents the relative strength of various possible arrangements of bolts.

Keywords: bolt, moment, rotation, stiffness, connections

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Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

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This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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Authors: Aqsa Jamil, Tamura Hiroshi, Katsuchi Hiroshi, Wang Jiaqi

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The yield point represents the upper limit of forces which can be applied to a specimen without causing any permanent deformation. After yielding, the behavior of the specimen suddenly changes, including the possibility of cracking or buckling. So, the accumulation of damage or type of fracture changes depending on this condition. As it is difficult to accurately detect yield points of the several stress concentration points in structural steel specimens, an effort has been made in this research work to develop a convenient technique using thermography (temperature-based detection) during tensile tests for the precise detection of yield point initiation. To verify the applicability of thermography camera, tests were conducted under different loading conditions and measuring the deformation by installing various strain gauges and monitoring the surface temperature with the help of a thermography camera. The yield point of specimens was estimated with the help of temperature dip, which occurs due to the thermoelastic effect during the plastic deformation. The scattering of the data has been checked by performing a repeatability analysis. The effects of temperature imperfection and light source have been checked by carrying out the tests at daytime as well as midnight and by calculating the signal to noise ratio (SNR) of the noised data from the infrared thermography camera, it can be concluded that the camera is independent of testing time and the presence of a visible light source. Furthermore, a fully coupled thermal-stress analysis has been performed by using Abaqus/Standard exact implementation technique to validate the temperature profiles obtained from the thermography camera and to check the feasibility of numerical simulation for the prediction of results extracted with the help of the thermographic technique.

Keywords: signal to noise ratio, thermoelastic effect, thermography, yield point

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Authors: Thomas Folegot, Arnaud Levaufre, Léna Bourven, Nicolas Kermagoret, Alexis Caillard, Roger Gallou

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Concern for negative impacts of anthropogenic noise on the ocean’s ecosystems has increased over the recent decades. This concern leads to a similar increased willingness to regulate noise-generating activities, of which shipping is one of the most significant. Dealing with ship noise requires not only knowledge about the noise from individual ships, but also how the ship noise is distributed in time and space within the habitats of concern. Marine mammals, but also fish, sea turtles, larvae and invertebrates are mostly dependent on the sounds they use to hunt, feed, avoid predators, during reproduction to socialize and communicate, or to defend a territory. In the marine environment, sight is only useful up to a few tens of meters, whereas sound can propagate over hundreds or even thousands of kilometers. Directive 2008/56/EC of the European Parliament and of the Council of June 17, 2008 called the Marine Strategy Framework Directive (MSFD) require the Member States of the European Union to take the necessary measures to reduce the impacts of maritime activities to achieve and maintain a good environmental status of the marine environment. The Ocean-Planner is a web-based platform that provides to regulators, managers of protected or sensitive areas, etc. with a decision support tool that enable to anticipate and quantify the effectiveness of management measures in terms of reduction or modification the distribution of underwater noise, in response to Descriptor 11 of the MSFD and to the Marine Spatial Planning Directive. Based on the operational sound modelling tool Quonops Online Service, Ocean-Planner allows the user via an intuitive geographical interface to define management measures at local (Marine Protected Area, Natura 2000 sites, Harbors, etc.) or global (Particularly Sensitive Sea Area) scales, seasonal (regulation over a period of time) or permanent, partial (focused to some maritime activities) or complete (all maritime activities), etc. Speed limit, exclusion area, traffic separation scheme (TSS), and vessel sound level limitation are among the measures supported be the tool. Ocean Planner help to decide on the most effective measure to apply to maintain or restore the biodiversity and the functioning of the ecosystems of the coastal seabed, maintain a good state of conservation of sensitive areas and maintain or restore the populations of marine species.

Keywords: underwater noise, marine biodiversity, marine spatial planning, mitigation measures, prediction

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Authors: Surajo Isa

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In as much as mathematics is important to national development, it is regrettable to note that in Nigeria Students academic achievement especially in public examinations remains poor. Among the several factors responsible for such a poor performance is the lack of bringing cultural elements into the conventional school mathematics. The design for this study is triangulation in nature which is set to examined 800 students From 20 School (40 each from male and female schools). Ten (10) male and ten (10) female schools consisting of 400 male and 400 female students to formed the experiment and control groups with a further sub-groping of samples to represent urban and rural settings for both male and female groups. While the experimental groups were taught using ethnomathematics techniques, the control groups were taught using conventional techniques, the results of a t-test for independent samples at p =0.05 level of significance with tcritical = 1.968 showed that (a) boys performed significantly better than girls (b) there is no significantly difference in performance between urban and rural girls (c) significant difference in academic performance was obtained between urban and rural boys. Generally, it was observed that teaching mathematics with ethnomathematics technique would help in great achievement in mathematics.

Keywords: ethnomathematics, achievement, gender, settlement

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Authors: Hashaam Akhtar

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IFNλR1 and IL10R2 collectively construct a heterodimer, which is an acknowledged functional receptor for all type III interferons (IFNs). Expression of IFNλR1 is highly tissue specific, which can help in making type III IFNs a drug of choice as comparable to its analogue, type I IFNs, for treating hepatitis C in the near future. Although, expression of IFNλR1 also varies with the concentration of type I IFNs, but in this study it was shown that the expression of IFNλR1 varies with the protein titers of IFN-α, IFN-λ3 and the newly discovered IFN-λ4. High dosage of IFN-α reduces the expression of IFNλR1 in HepG2 cells, which can affect the antiviral activity of type III IFNs in vivo. We premeditated an experimental strategy to differentiate monocytes into dendritic cells (DCs), type I and type II macrophages in vitro and quantified the expression of the IFNλR1 by qPCR. The exposure of newly discovered IFN-λ4 to macrophages and DCs also raised the expression of its own receptor, which shows that expression of IFN-λ4 protein in hepatitis C patient may augment type I treatment and help ease off viral titers. The results of this study may contribute in some understanding towards the mechanisms involved in the selective expression of IFNLR1 and exceptionalities associated with the receptor.

Keywords: IFNLR1, Interferon Lambda 4 (IFN-λ4), Mononuclear Phagocyte Cells (MPCs), expression

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Authors: Tokihiko Akita, Seiichi Mita

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A millimeter-wave radar is the most robust against adverse environments, making it an essential environment recognition sensor for automated driving. However, the reflection signal is sparse and unstable, so it is difficult to obtain the high recognition accuracy. Deep learning provides high accuracy even for them in recognition, but requires large scale datasets with ground truth. Specially, it takes a lot of cost to annotate for a millimeter-wave radar. For the solution, utilizing a simulator that can generate an annotated huge dataset is effective. Simulation of the radar is more difficult to match with real world data than camera image, and recognition by deep learning with higher-order features using the simulator causes further deviation. We have challenged to improve the accuracy of traffic participant classification by fusing simulator and real-world data with domain adaptation technique. Experimental results with the domain adaptation network created by us show that classification accuracy can be improved even with a few real-world data.

Keywords: millimeter-wave radar, object classification, deep learning, simulation, domain adaptation

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Authors: Nouf Alourfi

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This study examines the metabolism of amitriptyline (AMI) and verapamil (VER) using a KNIME-based method. KNIME improved workflow is an open-source data-analytics platform that integrates a number of open-source metabolomics tools such as CFMID and MetFrag to provide standard data visualisations, predict candidate metabolites, assess them against experimental data, and produce reports on identified metabolites. The use of this workflow is demonstrated by employing three types of liver microsomes (human, rat, and Guinea pig) to study the in vitro metabolism of the two drugs (AMI and VER). This workflow is used to create and treat UPLC-MS (Orbitrap) data. The formulas and structures of these drugs' metabolites can be assigned automatically. The key metabolic routes for amitriptyline are hydroxylation, N-dealkylation, N-oxidation, and conjugation, while N-demethylation, O-demethylation and N-dealkylation, and conjugation are the primary metabolic routes for verapamil. The identified metabolites are compatible to the published, clarifying the solidity of the workflow technique and the usage of computational tools like KNIME in supporting the integration and interoperability of emerging novel software packages in the metabolomics area.

Keywords: KNIME, CFMID, MetFrag, Data Analysis, Metabolomics

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Authors: Dawid Sołoducha, Tomasz Borowski, Marian Kordas, Rafał Rakoczy

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The magnetic field in the past few years became an important part of many studies. Magnetic field (MF) may be used to affect the process in many ways; for example, it can be used as a factor to stabilize the system. We can use MF to steer the operation, to activate or inhibit the process, or even to affect the vital activity of microorganisms. Using various types of magnetic field generators is always connected with the delivery of some heat to the system. Heat transfer is a very important phenomenon; it can influence the process positively and negatively, so it’s necessary to measure heat stream transferred from the place of generation and prevent negative influence on the operation. The aim of the presented work was to apply various types of magnetic fields and to measure heat transfer phenomena. The results were obtained by continuous measurement at several measuring points with temperature probes. Results were compilated in the form of temperature profiles. The study investigated the undetermined heat transfer in a custom system equipped with a magnetic field generator. Experimental investigations are provided for the explanation of the influence of the various type of magnetic fields on the heat transfer process. The tested processes are described by means of the criteria which defined heat transfer intensification under the action of magnetic field.

Keywords: heat transfer, magnetic field, undetermined heat transfer, temperature profile

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Authors: Miriam Sosa-Díaz, Faustino Sánchez-Garduño

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In population dynamics the study of both, the abundance and the spatial distribution of the populations in a given habitat, is a fundamental issue a From ecological point of view, the determination of the factors influencing such changes involves important problems. In this paper a mathematical model to describe the temporal dynamic and the spatiotemporal dynamic of the interaction of three populations (pollinators, plants and herbivores) is presented. The study we present is carried out by stages: 1. The temporal dynamics and 2. The spatio-temporal dynamics. In turn, each of these stages is developed by considering three cases which correspond to the dynamics of each type of interaction. For instance, for stage 1, we consider three ODE nonlinear systems describing the pollinator-plant, plant-herbivore and plant-pollinator-herbivore, interactions, respectively. In each of these systems different types of dynamical behaviors are reported. Namely, transcritical and pitchfork bifurcations, existence of a limit cycle, existence of a heteroclinic orbit, etc. For the spatiotemporal dynamics of the two mathematical models a novel factor are introduced. This consists in considering that both, the pollinators and the herbivores, move towards those places of the habitat where the plant population density is high. In mathematical terms, this means that the diffusive part of the pollinators and herbivores equations depend on the plant population density. The analysis of this part is presented by considering pairs of populations, i. e., the pollinator-plant and plant-herbivore interactions and at the end the two mathematical model is presented, these models consist of two coupled nonlinear partial differential equations of reaction-diffusion type. These are defined on a rectangular domain with the homogeneous Neumann boundary conditions. We focused in the role played by the density dependent diffusion term into the coexistence of the populations. For both, the temporal and spatio-temporal dynamics, a several of numerical simulations are included.

Keywords: bifurcation, heteroclinic orbits, steady state, traveling wave

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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Authors: Innocent C. Ezenwa, Takashi Yoshino

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Knowledge of the transport properties of Fe and its alloys at extreme high pressure (P), temperature (T) conditions are essential for understanding the generation and sustainability of the magnetic field of the rocky planets with a metallic core. Since Pt, an unfilled d-band late transition metal with an electronic structure of Xe4f¹⁴5d⁹6s¹, is paramagnetic and remains close-packed structure at ambient conditions and high P-T, it is expected that its transport properties at these conditions would be similar to those of ε-Fe. We investigated the T-dependent electrical resistivity of solid and liquid Pt up to 8 GPa and found it constant along its melting curve both on the liquid and solid sides in agreement with theoretical prediction and experimental results estimated from thermal conductivity measurements. Our results suggest that the T-dependent resistivity of ε-Fe is linear and would not saturate at high P, T conditions. This, in turn, suggests that the thermal conductivity of liquid Fe at Earth’s core conditions may not be as high as previously suggested by models employing saturation resistivity. Hence, thermal convection could have powered the geodynamo before the birth of the inner core. The electrical resistivity and thermal conductivity on the liquid and solid sides of the inner core boundary of the Earth would be significantly different in values.

Keywords: electrical resistivity, thermal conductivity, transport properties, geodynamo and geomagnetic field

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Authors: Issa Qabaja, Fadi Thabtah

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Email phishing classification is one of the vital problems in the online security research domain that have attracted several scholars due to its impact on the users payments performed daily online. One aspect to reach a good performance by the detection algorithms in the email phishing problem is to identify the minimal set of features that significantly have an impact on raising the phishing detection rate. This paper investigate three known feature selection methods named Information Gain (IG), Chi-square and Correlation Features Set (CFS) on the email phishing problem to separate high influential features from low influential ones in phishing detection. We measure the degree of influentially by applying four data mining algorithms on a large set of features. We compare the accuracy of these algorithms on the complete features set before feature selection has been applied and after feature selection has been applied. After conducting experiments, the results show 12 common significant features have been chosen among the considered features by the feature selection methods. Further, the average detection accuracy derived by the data mining algorithms on the reduced 12-features set was very slight affected when compared with the one derived from the 47-features set.

Keywords: data mining, email classification, phishing, online security

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

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Authors: Lingaraju Dumpala, Laxmi Mohan Kumar Chintada, Devadas Deepu, Pravin Kumar Yadav

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Friction stir welding is the new-fangled and cutting-edge technique in welding applications; it is widely used in the fields of transportation, aerospace, defense, etc. For thriving significant welding joints and properties of friction stir welded components, it is essential to carry out this advanced process in a prescribed systematic procedure. At this moment, Underwater Friction Stir Welding (UFSW) Process is the field of interest to do research work. In the continuous assessment, the study of UFSW process is to comprehend problems occurred in the past and the structure through which the mechanical properties of the welded joints can be value-added and contributes to conclude results an acceptable and resourceful joint. A meticulous criticism is given on how to modify the experimental setup from NFSW to UFSW. It can discern the influence of tool materials, feeds, spindle angle, load, rotational speeds and mechanical properties. By expending the DEFORM-3D simulation software, the achieved outcomes are validated.

Keywords: Underwater Friction Stir Welding(UFSW), Al alloys, mechanical properties, Normal Friction Stir Welding(NFSW)

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Authors: Valerio D’Andrea

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The GERmanium Detector Array (GERDA) experiment, located at the Laboratori Nazionali del Gran Sasso (LNGS) of INFN, searches for 0νββ of 76Ge. Germanium diodes enriched to ∼ 86 % in the double beta emitter 76Ge(enrGe) are exposed being both source and detectors of 0νββ decay. Neutrinoless double beta decay is considered a powerful probe to address still open issues in the neutrino sector of the (beyond) Standard Model of particle Physics. Since 2013, just after the completion of the first part of its experimental program (Phase I), the GERDA setup has been upgraded to perform its next step in the 0νββ searches (Phase II). Phase II aims to reach a sensitivity to the 0νββ decay half-life larger than 1026 yr in about 3 years of physics data taking. This exposing a detector mass of about 35 kg of enrGe and with a background index of about 10^−3 cts/(keV·kg·yr). One of the main new implementations is the liquid argon scintillation light read-out, to veto those events that only partially deposit their energy both in Ge and in the surrounding LAr. In this paper, the GERDA Phase II expected goals, the upgrade work and few selected features from the 2015 commissioning and 2016 calibration runs will be presented. The main Phase I achievements will be also reviewed.

Keywords: gerda, double beta decay, LNGS, germanium

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Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, Meisam Babaie

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Gas lift optimization is becoming more important now a day in petroleum industry. A proper lift optimization can reduce the operating cost, increase the net present value (NPV) and maximize the recovery from the asset. A widely accepted definition of gas lift optimization is to obtain the maximum output under specified operating conditions. In addition, gas lift, a costly and indispensable means to recover oil from high depth reservoir entails solving the gas lift optimization problems. Gas lift optimization is a continuous process; there are two levels of production optimization. The total field optimization involves optimizing the surface facilities and the injection rate that can be achieved by standard tools softwares. Well level optimization can be achieved by optimizing the well parameters such as point of injection, injection rate, and injection pressure. All these aspects have been investigated and presented in this study by using experimental data and PROSPER simulation program. The results show that the well head pressure has a large influence on the gas lift performance and also proved that smart gas lift valve can be used to improve gas lift performance by controlling gas injection from down hole. Obtaining the optimum gas injection rate is important because excessive gas injection reduces production rate and consequently increases the operation cost.

Keywords: optimization, production rate, reservoir pressure effect, gas injection rate effect, gas injection pressure

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Authors: Young-Taeg Kim, Gwang Ho Seo, Hyungju Oh, Ho Kyung Ha, Kuk Jin Kim

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Kim et al., hypothesized an increase in volume transport in the Korea Strait based on the concurrent increase in water temperature and mean sea level observed by the Korea Hydrographic and Oceanographic Agency (KHOA) in the vicinity of the Korea Strait from 2000 to 2009. Since then, to our best knowledge, no definitive studies have been reported on the increase in volume transport through the Korea Strait, but the observed water temperature (2000-2021) and sea level (1989-2021) in the Korea Strait and East Sea have been found to be increasing. In particular, the rapid increase rate in the mean sea level rise (2.55~3.53 mm/y) in these areas cannot be explained by only steric effect due to the increased water temperature. It is more reasonable interpretation that the sea level rise is due to an increase in the volume transport of warm and salty currents. If the increase in the volume transport is explained by the geostrophic equation without considering the sea level rise in the Korea Strait, the current velocity should increase. However, up to now, there are no reports of an increase in current velocity from direct observations using ADCP (e.g., observations of Camellia) or from various numerical models. Therefore, the increase in volume transport cannot be explained by the geostrophic equation. Another possible explanation for the increase in the volume transport is the effect of wind. Although Korea is dominated by monsoon, it is affected by winds according to El Niño and La Niña, which have a cycle of about 3 to 4 years. During El Niño (La Niña), northerly winds (southerly winds) prevail in Korea. Consequently, it is inferred that the transported volume in the Korea Strait slowly increases interannually. However, in this study, it was difficult to find a clear correlation between annually-averaged mean sea level and El Niño (or La Niña) during 1989-2021. This is probably due to the interactions of the PDO (Pacific Decadal Oscillation) and AO (Arctic Oscillation) along with the ENSO (El niño-Southern Oscillation). However, it is clear that the interannual variability of winds is affecting the volume transport in the Korean Strait. On the other hand, the effect of global sea level rise on the volume transport in the Korea Strait is small compared to the interannual variability of the volume transport, but it seems to play a constant role.

Keywords: mean sea level, volume transport, El nino, La nina

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Authors: Víctor Martínez del Rey, Kourosh Nasr Esfahani, Amir Masoud Samani Majd

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In this experimental study, the behaviors of Mixed Oxidant solution components (MOS) and sodium hypochlorite (HYPO) as the most commonly applied surface disinfectant were compared through the effectiveness of chlorine disinfection as a function of the contact time and residual chlorine. In this regard, the variation of pH, free available chlorine (FAC) concentration, and electric conductivity (EC) of disinfection solutions in different concentrations were monitored over 48 h contact time. In parallel, the plant stress activated by chlorine-based disinfectants was assessed by comparing MOS and HYPO. The elements of pH and EC in the plant-soil and their environmental impacts, spread by disinfection solutions were analyzed through several concentrations of FAC including 500 mg/L, 1000 mg/L, and 5000 mg/L in irrigated water. All the experiments were carried out at the service station of Sant Cugat, Spain. The outcomes indicated lower pH and higher durability of MOS than HYPO at the same concentration of FAC which resulted in promising stability of FAC within MOS. Furthermore, the pH and EC value of plant-soil irrigated by NaOCl solution were higher than that of MOS solution at the same FAC concentration. On-site generation of MOS as a safe chlorination option might be considered an imaginary future of smart cities.

Keywords: disinfection, free available chlorine, on-site generation, sodium hypochlorite

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Hsin-Yu Lee, Ming-Zhong Li, Wen-Hsi Chiu, Su-Fen Cheng, Shwu-Wen Lin

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Background: The use of medical terminology is essential to professional nurses on clinical practice. However, most nursing students consider traditional lecture-based teaching of medical terminology as boring and overly conceptual and lack motivation to learn. It is thus an issue to be discussed on how to enhance nursing students’ self-directed learning and improve learning outcomes of medical terminology. Digital game-based learning is a learner-centered way of learning. Past literature showed that the most common game-based learning for language education has been immersive games and teaching games. Thus, this study selected role-playing games (RPG) and digital puzzle games for observation and comparison. It is interesting to explore whether digital game-based learning has positive impact on nursing students’ learning of medical terminology and whether students can adapt well on this type of learning. Results can be used to provide references for institutes and teachers on teaching medical terminology. These instructions give you guidelines for preparing papers for the conference. Use this document as a template if you are using Microsoft Word. Otherwise, use this document as an instruction set. The electronic file of your paper will be formatted further at WASET. Define all symbols used in the abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets the footnote at the bottom of this column. Page margins are 1,78 cm top and down; 1,65 cm left and right. Each column width is 8,89 cm and the separation between the columns is 0,51 cm. Objective: The purpose of this research is to explore respectively the impact of RPG and puzzle game on nursing students’ self-directed learning and technology acceptance. The study further discusses whether different game types bring about different influences on students’ self-directed learning and technology acceptance. Methods: A quasi-experimental design was adopted in this study so that repeated measures between two groups could be conveniently conducted. 103 nursing students from a nursing college in Northern Taiwan participated in the study. For three weeks of experiment, the experiment group (n=52) received “traditional teaching + RPG” while the control group (n=51) received “traditional teaching + puzzle games”. Results: 1. On self-directed learning: For each game type, there were significant differences for the delayed tests of both groups as compared to the pre and post-tests of each group. However, there were no significant differences between the two game types. 2. On technology acceptance: For the experiment group, after the intervention of RPG, there were no significant differences concerning technology acceptance. For the control group, after the intervention of puzzle games, there were significant differences regarding technology acceptance. Pearson-correlation coefficient and path analysis conducted on the results of the two groups revealed that the dimension were highly correlated and reached statistical significance. Yet, the comparison of technology acceptance between the two game types did not reach statistical significance. Conclusion and Recommend: This study found that through using different digital games on learning, nursing students have effectively improved their self-directed learning. Students’ technology acceptances were also high for the two different digital game types and each dimension was significantly correlated. The results of the experimental group showed that through the scenarios of RPG, students had a deeper understanding of medical terminology, which reached the ‘Understand’ dimension of Bloom’s taxonomy. The results of the control group indicated that digital puzzle games could help students memorize and review medical terminology, which reached the ‘Remember’ dimension of Bloom’s taxonomy. The findings suggest that teachers of medical terminology could use digital games to assist their teaching according to their goals on cognitive learning. Adequate use of those games could help improve students’ self-directed learning and further enhance their learning outcome on medical terminology.

Keywords: digital game-based learning, medical terminology, nursing education, self-directed learning, technology acceptance model

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Authors: S. Altmeyer, B. Hof, F. Marques, J. M. Lopez

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We present numerical simulations concerning the reversal of spiraling vortices in short highly counter-rotating cylinders. Increasing the differential cylinder rotation results in global flow-inversion is which develops various different and complex flow dynamics of several quasi-periodic solutions that differ in their number of vortex cells in the bulk. The dynamics change from being dominated of the inner cylinder boundary layer with ’passive’ only responding outer one to be dominated by the outer cylinder boundary layer with only responding inner one. Solutions exist on either two or three tori invariant manifolds whereby they appear as symmetric or asymmetric states. We find for either moderate and high inner cylinder rotation speed the quasiperiodic flow to consist of only two vortex cells but differ as the vortices has opposite spiraling direction. These both flows live on 2-tori but differ in number of symmetries. While for the quasi-periodic flow (q^a_2) at lower rotation speed a pair of symmetrically related 2-tori T2 exists the quasi-periodic flow (q^s_2) at higher rotation speeds is symmetric living on a single 2-torus T2. In addition these both flows differ due to their dominant azimuthal m modes. The first is dominated by m=1 whereas for the latter m=3 contribution is largest. The 2-tori states are separated by a further quasi-periodic flow (q^a_3) living on pair of symmetrically related 3-tori T3. This flow offers a ’periodical’ competition between a two and three vortex cell states in the bulk. This flow is also an m=1 solution as for the quasiperiodic flows living on the pair of symmetrically-related 2-tori states. Moreover we find hysteresis resulting in coexisting regions of different quasiperiodic flows q^s_2 and q^a_3 with increasing and decreasing the differential rotation.

Keywords: transition, bifurcation, torus, symmetries

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Authors: Mojtaba Valinataj

Abstract:

Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

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Authors: Amritansh Agarwal, Tejaswi Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

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Authors: Olga A. Burukina

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Tourism is a complex socio-economic phenomenon, partly regulated by national tourism industries. The sustainable development of tourism in a region, country or in tourist destination depends on a number of factors (political, economic, social, cultural, legal and technological), the understanding and correct interpretation of which is invariably anthropocentric. It is logical that for the successful functioning of a tour operating company, it is necessary to ensure its sustainable development. Sustainable tourism is defined as tourism that fully considers its current and future economic, social and environmental impacts, taking into account the needs of the industry, the environment and the host communities. For the business enterprise, sustainable development is defined as adopting business strategies and activities that meet the needs of the enterprise and its stakeholders today while protecting, sustaining and enhancing the human and natural resources that will be needed in the future. In addition to a systemic approach to the analysis of tourist destinations, each tourism project can and should be considered as a system characterized by a very high degree of variability, since each particular case of its implementation differs from the previous and subsequent ones, sometimes in a cardinal way. At the same time, it is important to understand that this variability is predominantly of anthropogenic nature (except for force majeure situations that are considered separately and afterwards). Knowledge management is the process of creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organisational objectives by making the best use of knowledge. Knowledge management is seen as a key systems component that allows obtaining, storing, transferring, and maintaining information and knowledge in particular, in a long-term perspective. The study aims, firstly, to identify (1) the dynamic changes in the Italian travel industry in the last 5 years before the COVID19 pandemic, which can be considered the scope of force majeure circumstances, (2) the impact of the pandemic on the industry and (3) efforts required to restore it, and secondly, how project management tools can help to improve knowledge management in tour operating companies to maintain their sustainability, diminish potential risks and restore their pre-pandemic performance level as soon as possible. The pilot research is based upon a systems approach and has employed a pilot survey, semi-structured interviews, prior research analysis (aka literature review), comparative analysis, cross-case analysis, and modelling. The results obtained are very encouraging: PM tools can improve knowledge management in tour operating companies and secure the more sustainable development of the Italian tourism industry based on proper knowledge management and risk management.

Keywords: knowledge management, project management, sustainable development, tourism industr

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Authors: A. Falavand Jozaei, A. Ghafouri

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Operation enhancement in an air cooler (heat exchanger) depends on the rate of heat transfer, and pressure drop. In this paper, for a given heat duty, study of the effects of FPI (fin per inch) and fin type (circular and hexagonal fins) on two parameters mentioned above is considered in an air cooler in Iran, Arvand petrochemical. A program in EES (Engineering Equations Solver) software moreover, Aspen B-JAC and HTFS+ software are used for this purpose to solve governing equations. At first the simulated results obtained from this program is compared to the experimental data for two cases of FPI. The effects of FPI from 3 to 15 over heat transfer (Q) to pressure drop ratio (Q/Δp ratio). This ratio is one of the main parameters in design, rating, and simulation heat exchangers. The results show that heat transfer (Q) and pressure drop increase with increasing FPI (fin per inch) steadily, and the Q/Δp ratio increases to FPI = 12 (for circular fins about 47% and for hexagonal fins about 69%) and then decreased gradually to FPI = 15 (for circular fins about 5% and for hexagonal fins about 8%), and Q/Δp ratio is maximum at FPI = 12. The FPI value selection between 8 and 12 obtained as a result to optimum heat transfer to pressure drop ratio. Also by contrast, between circular and hexagonal fins results, the Q/Δp ratio of hexagonal fins more than Q/Δp ratio of circular fins for FPI between 8 and 12 (optimum FPI).

Keywords: air cooler, circular and hexagonal fins, fin per inch, heat transfer and pressure drop

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Authors: Reena Murali, David Peter S.

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The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies shows that up regulation of mRNA cause serious diseases like Cancer. So designing effective siRNA with good knockdown effects play an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (ΔG), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: artificial neural network, double stranded RNA, RNA interference, short interfering RNA

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Authors: Malika Souada, Juanita Rausch, Benjamin Guinot, Christine Bugajny

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The increase of global commerce and tourism makes the shipping sector an important contributor of atmospheric pollution. Both, airborne particles and gaseous pollutants have negative impact on health and climate. This is especially the case in port cities, due to the proximity of the exposed population to the shipping emissions in addition to other multiple sources of pollution linked to the surrounding urban activity. The objective of this study is to determine the concentrations of fine particles (immission), specifically PM2.5, PM1, PM0.3, BC and sulphates, in a context where maritime passenger traffic plays an important role (port area of Bordeaux centre). The methodology is based on high temporal resolution measurements of pollutants, correlated with meteorological and ship movements data. Particles and gaseous pollutants from seven maritime passenger ships were sampled and analysed during the docking, manoeuvring and berthing phases. The particle mass measurements were supplemented by measurements of the number concentration of ultrafine particles (<300 nm diameter). The different measurement points were chosen by taking into account the local meteorological conditions and by pre-modelling the dispersion of the smoke plumes. The results of the measurement campaign carried out during the summer of 2021 in the port of Bordeaux show that the detection of concentrations of particles emitted by ships proved to be punctual and stealthy. Punctual peaks of ultrafine particle concentration in number (P#/m3) and BC (ng/m3) were measured during the docking phases of the ships, but the concentrations returned to their background level within minutes. However, it appears that the influence of the docking phases does not significantly affect the air quality of Bordeaux centre in terms of mass concentration. Additionally, no clear differences in PM2.5 concentrations between the periods with and without ships at berth were observed. The urban background pollution seems to be mainly dominated by exhaust and non-exhaust road traffic emissions. However, temporal high-resolution measurements suggest a probable emission of gaseous precursors responsible for the formation of secondary aerosols related to the ship activities. This was evidenced by the high values of the PM1/BC and PN/BC ratios, tracers of non-primary particle formation, during periods of ship berthing vs. periods without ships at berth. The research findings from this study provide robust support for port area air quality assessment and source apportionment.

Keywords: characterization, fine particulate matter, harbour air quality, shipping impacts

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Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

Abstract:

Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks

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