Search results for: approximate dynamic programming

Authors: Fayssal Amrane, Azeddine Chaiba, Bruno Francois

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In this paper, design and experimental study based on Direct Power Control (DPC) of DFIG is proposed for Stand-alone mode in Variable Speed Wind Energy Conversion System (VS-WECS). The proposed IDPC method based on robust IP (Integral-Proportional) controllers in order to control the Rotor Side Converter (RSC) by the means of the rotor current d-q axes components (Ird* and Irq*) of Doubly Fed Induction Generator (DFIG) through AC-DC-AC converter. The implementation is realized using dSPACE dS1103 card under Sub and Super-synchronous operations (means < and > of the synchronous speed “1500 rpm”). Finally, experimental results demonstrate that the proposed control using IP provides improved dynamic responses, and decoupled control of the wind turbine has driven DFIG with high performances (good reference tracking, short response time and low power error) despite for sudden variation of wind speed and rotor references currents.

Keywords: Direct Power Control (DPC), Doubly fed induction generator (DFIG), Wind Energy Conversion System (WECS), Experimental study.

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Authors: Ziraguen O. Williams, Shield B. Lin, Fouad N. Matari, Leslie J. Quiocho

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In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, feedback delay, and signal noise were added to a simulation model of an active-controlled vibration isolation system to regulate the movement of the exercise platform. Previous simulation work was conducted primarily via MATLAB/Simulink. Two additional simulation tools used in this study were Trick and MBDyn, NASA co-developed software simulation environments. Simulation results obtained from these three tools were very similar. All simulation results support the hypothesis that an active-controlled vibration isolation system outperforms a passive-controlled system even with the addition of feedback delay and signal noise to the active-controlled system. In this paper, squat exercise was used in creating excited force to the simulation model. The exciter force from a squat exercise was calculated from the motion capture of an exerciser. The simulation results demonstrate much greater transmitted force reduction in the active-controlled system than the passive-controlled system.

Keywords: control, counterweight, isolation, vibration

Procedia PDF Downloads 111

Authors: Alexander V. Spirov, David M. Holloway, Ekaterina M. Myasnikova

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Segmentation of the early Drosophila embryo results from the dynamic establishment of spatial gene expression patterns. Patterning occurs on an embryo geometry which is a 'deformed' prolate ellipsoid, with anteroposterior and dorsal-ventral major and minor axes, respectively. Patterning is largely independent along each axis, but some interaction can be seen in the 'bending' of the segmental expression stripes. This interaction is not well understood. In this report, we investigate how 3D geometrical features of the early embryo affect the segmental expression patterning. Specifically, we study the effect of geometry on formation of the Bicoid primary morphogenetic gradient. Our computational results demonstrate that embryos with a much longer ventral than dorsal surface ('bellied') can produce curved Bicoid concentration contours which could activate curved stripes in the downstream pair-rule segmentation genes. In addition, we show that having an extended source for Bicoid in the anterior of the embryo may be necessary for producing the observed exponential form of the Bicoid gradient along the anteroposterior axis.

Keywords: Drosophila embryo, bicoid morphogenetic gradient, exponential expression profile, expression surface form, segmentation genes, 3D modelling

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Authors: Duy M. P. Vo, Cornelia Sennewald, Gerald Hoffmann, Chokri Cherif

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The development of solutions to improve the resistance of buildings to short-term dynamic loads, particularly impact load, is driven by the urgent demand worldwide on securing human life and critical infrastructures. The research training group GRK 2250/1 aims to develop mineral-bonded composites that allow the fabrication of thin-layered strengthening layers providing available concrete members with enhanced impact resistance. This paper presents the development of 3D woven wire cellular structures that can be used as innovative reinforcement for targeted composites. 3D woven wire cellular structures are truss-like architectures that can be fabricated in an automatized process with a great customization possibility. The specific architecture allows this kind of structures to have good load bearing capability and forming behavior, which is of great potential to give strength against impact loading. An appropriate combination of topology and material enables an optimal use of thin-layered reinforcement in concrete constructions.

Keywords: 3D woven cellular structures, ductile behavior, energy absorption, fiber-based reinforced concrete, impact resistant

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Authors: Amir Jalalian-Khakshour, T. N. Croft

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Vertical Axis Wind Turbine (VAWT) systems are becoming increasingly popular as they have a number of advantages over traditional wind turbines. The advantages are reliability, ease of transportation and manufacturing. These attributes could make these technologies useful in developing economies. The performance characteristics of a VAWT are different from a horizontal axis wind turbine, which can be attributed to the low tip speed ratio operation. To unlock the potential of these VAWT systems, the operational behaviour in a number of system topologies and environmental conditions needs to be understood. In this study, a non-linear dynamic simulation method was developed in Matlab and validated against in field data of a large scale, 8-meter rotor diameter prototype. This simulation method has been utilised to determine the performance characteristics of a number of control methods and system topologies. The motivation for this research was to develop a simulation method which accurately captures the operating behaviour and is computationally inexpensive. The model was used to evaluate the performance through parametric studies and optimisation techniques. The study gave useful insights into the applications and energy generation potential of this technology.

Keywords: power generation, renewable energy, rotordynamics, wind energy

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Authors: Shipra Sharma, Jagat Jerath

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Human resource training is an essential element of talent management in the current era of global competitiveness and dynamic trade in the manufacturing industry. Globally, India is behind only China as the largest textile manufacturer. The major challenges faced by the Indian textile manufacturing Industry are low technology levels, growing skill gaps, unorganized structure, lower efficiencies, etc. indicating the need for constant talent up-gradation. Assessment of training needs from a strategic perspective is an essential step for the formulation of effective training. The paper established the significance of training in the Indian textile industry and to determine the training needs on various parameters as presented. 40 HR personnel/s working in the textile and apparel companies based in the industrial region of Punjab, India, were the respondents for the study. The research tool used in this case was a structured questionnaire as per five-point Likert scale. Statistical analysis through descriptive statistics and chi-square test indicated the increased need for training whenever there were technical changes in the organizations. As per the data presented in this study, most of the HR personnel/s agreed that the variables associated with organizational analysis, task analysis, and individual analysis have a statistically significant role to play in determining the need for training in an organization.

Keywords: Indian textile manufacturing industry, significance of training, training needs analysis, parameters for training needs assessment

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Authors: Faghihnia Torshizi Mostafa, Saitoh Masato

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An efficient method is developed for the response of a group of vertical, cylindrical fixed-head, finite length piles embedded in a homogeneous elastic stratum, subjected to harmonic force atop the pile group cap. Pile to pile interaction is represented through simplified beam-on-dynamic-Winkler-foundation (BDWF) with realistic frequency-dependent springs and dashpots. Pile group effect is considered through interaction factors. New closed-form expressions for interaction factors and curvature ratios atop the pile are extended by considering different boundary conditions at the tip of the piles (fixed, hinged). In order to investigate the fundamental characteristics of inertial bending strains in pile groups, inertial bending strains at the head of each pile are expressed in terms of slenderness ratio. The results of parametric study give valuable insight in understanding the behavior of fixed head pile groups in fundamental natural frequency of soil stratum.

Keywords: Winkler-foundation, fundamental frequency of soil stratum, normalized inertial bending strain, harmonic excitation

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Authors: Omer Burak Iskender, Keck Voon Ling, Vincent Dubanchet, Luca Simonini

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This paper presents Guidance and Control (G&C) strategy to approach and synchronize with potentially rotating targets. The proposed strategy generates and tracks a safe trajectory for space servicing missions, including tasks like approaching, inspecting, and capturing. The main objective of this paper is to validate the G&C laws using a Hardware-In-the-Loop (HIL) setup with realistic rendezvous and docking equipment. Throughout this work, the assumption of full relative state feedback is relaxed by onboard sensors that bring realistic errors and delays and, while the proposed closed loop approach demonstrates the robustness to the above mentioned challenge. Moreover, G&C blocks are unified via the Model Predictive Control (MPC) paradigm, and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. In this work, G&C is formulated as a convex optimization problem where constraints such as thruster limits and the output constraints are explicitly handled. Furthermore, the Monte-Carlo method is used to evaluate the robustness of the proposed method to the initial condition errors, the uncertainty of the target's motion and attitude, and actuator errors. A capture scenario is tested with the robotic test bench that has onboard sensors which estimate the position and orientation of a drifting satellite through camera imagery. Finally, the approach is compared with currently used robust H-infinity controllers and guidance profile provided by the industrial partner. The HIL experiments demonstrate that the proposed strategy is a potential candidate for future space servicing missions because 1) the algorithm is real-time implementable as convex programming offers deterministic convergence properties and guarantee finite time solution, 2) critical physical and output constraints are respected, 3) robustness to sensor errors and uncertainties in the system is proven, 4) couples translational motion with rotational motion.

Keywords: dual quaternion, model predictive control, real-time experimental test, rendezvous and docking, spacecraft autonomy, space servicing

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Authors: Doo W. Lee, Soo J. Lee, Bye R. Yoon, Jae Y. Jho, Kyehan Rhee

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Hand exoskeletons have been developed in order to assist daily activities for disabled and elder people. A figure exoskeleton was developed using ionic polymer metal composite (IPMC) actuators, and the performance of it was evaluated in this study. In order to study dynamic performance of a finger dummy performing pinching motion, force generating characteristics of an IPMC actuator and pinching motion of a thumb and index finger dummy actuated by IMPC actuators were analyzed. The blocking force of 1.54 N was achieved under 4 V of DC. A thumb and index finger dummy, which has one degree of freedom at the proximal joint of each figure, was manufactured by a three dimensional rapid prototyping. Each figure was actuated by an IPMC actuator, and the maximum fingertip force was 1.18 N. Pinching motion of a dummy was analyzed by two video cameras in vertical top and horizontal left end view planes. A figure dummy powered by IPMC actuators could perform flexion and extension motion of an index figure and a thumb.

Keywords: finger exoskeleton, ionic polymer metal composite, flexion and extension, motion analysis

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: D. Suman, B. Nikitha, J. Sarvani, V. Archana

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Histological slides provide clinical diagnostic information about the subjects from the ancient times. Even with the advent of high resolution imaging cameras the image tend to have some background noise which makes the analysis complex. A study of the histological slides is done by using a nonlinear transfer function based image enhancement method. The method processes the raw, color images acquired from the biological microscope, which, in general, is associated with background noise. The images usually appearing blurred does not convey the intended information. In this regard, an enhancement method is proposed and implemented on 50 histological slides of human tissue by using nonlinear transfer function method. The histological image is converted into HSV color image. The luminance value of the image is enhanced (V component) because change in the H and S components could change the color balance between HSV components. The HSV image is divided into smaller blocks for carrying out the dynamic range compression by using a linear transformation function. Each pixel in the block is enhanced based on the contrast of the center pixel and its neighborhood. After the processing the V component, the HSV image is transformed into a colour image. The study has shown improvement of the characteristics of the image so that the significant details of the histological images were improved.

Keywords: HSV space, histology, enhancement, image

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Authors: Lucksini Raveendran

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Introduction: This mixed-methods study focuses on the experiences of ethnocultural youth and families in Canada, identifying key barriers and opportunities to inform service programming and policies that can better meet their mental health needs during the COVID-19 pandemic and beyond. Methods: Mental Health Commission of Canada's Headstrong initiative administered the youth survey (April – June 2020) and family survey (June – August 2020) with a total sample size of 137 and 481 respondents, respectively. Thematic analysis was conducted to identify key challenges faced, coping strategies used, and help-seeking behaviours. A similar approach was also applied to the family survey data, but instead, a representative sample was collated to analyze geographically variable and ethnically diverse subgroups. Results and analysis: Multiple challenges have impacted families, including increased feelings of loneliness and distress from border travel restrictions, especially among those navigating pregnancy alone or managing children with developmental needs, which is often understudied. Also, marginalized groups were disproportionately affected by inequitable access to communication technologies, further deepening the digital divide. Some reported living in congregated homes with regular conflicts, thus leading to increased anxiety and exposure to violence. For many families, urbanicity and ethnicity played a key role in how families reported coping with feelings of uncertainty while managing work commitments, navigating community resources, fulfilling care responsibilities, and homeschooling children of all ages. Despite these challenges, there was evidence of post-traumatic growth and building community resiliency. Conclusions and implications for policy, practice, or additional research: There is a need to foster opportunities to promote and sustain mental health, wellness, and resilience for families through social connections. Also, intersectionality must be embedded in the collection, analysis, and application of data to improve equitable access to evidence-based and recovery-oriented mental health supports among diverse families in Canada. Lastly, address future research on the long-term COVID-19 impacts of travel border restrictions on family wellness.

Keywords: mental health, youth mental health, family wellness, health equity

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Authors: Guantao Bai

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Public space is an indispensable and important component of the urban built environment. How to more accurately evaluate the usage characteristics of public space can help improve its spatial quality. Compared to traditional survey methods, computer vision technology based on deep learning has advantages such as dynamic observation and low cost. This study takes the public space of Shaping Park as an example and, based on deep learning computer vision technology, processes and analyzes the image data of the public space to obtain the spatial usage characteristics and spatiotemporal characteristics of the public space. Research has found that the spontaneous activity time in public spaces is relatively random with a relatively short average activity time, while social activities have a relatively stable activity time with a longer average activity time. Computer vision technology based on deep learning can effectively describe the spatial usage characteristics of the research area, making up for the shortcomings of traditional research methods and providing relevant support for creating a good public space.

Keywords: computer vision, deep learning, public spaces, using features

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Authors: Rupesh S. Gundewar, Kanchan C. Khare

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Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: Chunying Fang, Haifeng Li, Lin Ma, Mancai Zhang

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Speech intelligibility assessment is an important measure to evaluate the functional outcomes of surgical and non-surgical treatment, speech therapy and rehabilitation. The assessment of pathological speech plays an important role in assisting the experts. Pathological speech usually is non-stationary and mutational, in this paper, we describe a multi-granularity combined feature schemes, and which is optimized by hierarchical visual method. First of all, the difference granularity level pathological features are extracted which are BAFS (Basic acoustics feature set), local spectral characteristics MSCC (Mel s-transform cepstrum coefficients) and nonlinear dynamic characteristics based on chaotic analysis. Latterly, radar chart and F-score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96-dimensions.The experimental results denote that new features by support vector machine (SVM) has the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.

Keywords: pathological speech, multi-granularity feature, MSCC (Mel s-transform cepstrum coefficients), F-score, radar chart

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Authors: Libo Jiang, Huan Li, Rongling Wu

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Ordinary differentiation equations (ODE) have proven to be powerful for reconstructing precise and informative gene regulatory networks (GRNs) from dynamic gene expression data. However, joint modeling and analysis of all genes, essential for the systematical characterization of genetic interactions, are challenging due to high dimensionality and a complex pattern of genetic regulation including activation, repression, and antitermination. Here, we address these challenges by unifying variable selection and game theory through ODE. Each gene within a GRN is co-expressed with its partner genes in a way like a game of multiple players, each of which tends to choose an optimal strategy to maximize its “fitness” across the whole network. Based on this unifying theory, we designed and conducted a real experiment to infer salt tolerance-related GRNs for Euphrates poplar, a hero tree that can grow in the saline desert. The pattern and magnitude of interactions between several hub genes within these GRNs were found to determine the capacity of Euphrates poplar to resist to saline stress.

Keywords: gene regulatory network, ordinary differential equation, game theory, LASSO, saline resistance

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Authors: Igor V. Kuzminov

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The proposed article is a development of the topics of gravity, the inverse temperature dependence of gravity, the action of the inverse temperature dependence of gravity, and the second law of thermodynamics, dark matter, the identity of gravity, inertial forces, and centrifugal forces. All interaction schemes are built on the basis of Newton's laws of classical mechanics and Rutherford's planetary model of the structure of the atom. The basis of all constructions is the gyroscopic effect of rotation of all particles of the atomic structure. In this case, interatomic and intermolecular bonds are accepted as the static part of the gyroscope, and the rotation of an electron in an atom is accepted as the dynamic part. The structure of the planet Earth is accepted as a model of the structure of the Black Hole. Namely, gravitational and thermodynamic phenomena in the structure of the planet Earth are accepted as a model. Based on this model, assumptions are made about the processes inside the Black Hole. Moreover, a version is put forward, a scheme of a closed cycle of transformation of matter in the Universe.

Keywords: black hole, gravity, inverse temperature dependence of gravitational forces, second law of thermodynamics, gyroscopic effect, dark matter

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Authors: Kexin Chen

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As an important method of transportation to solve the demand and supply contradiction generated in the rapid urbanization process, urban rail traffic system has been rapidly developed over the past ten years in China. During the rapid development, the space of urban rail Transit has encountered many problems, such as space simplification, sensory experience dullness, and poor regional identification, etc. This paper, focus on the study of the negative space of subway station and spatial softening, by comparing and learning from foreign cases. The article sorts out cases at home and abroad, make a comparative study of the cases, analysis more diversified setting of public art, and sets forth propositions on the domestic type of public art in the space of urban rail transit for reference, then shows the relationship of the spatial attribute in the space of urban rail transit and public art form. In this foundation, it aims to characterize more diverse setting ways for public art; then suggests the three public art forms corresponding properties, such as static presenting mode, dynamic image mode, and spatial softening mode; finds out the method of urban public art to optimize negative space.

Keywords: diversification, negative space, optimization strategy, public art planning

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Authors: A. Moualdia, D. J. Boudana, O. Bouchhida, A. Medjber

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, the cost of this energy is still too high to compete with traditional fossil fuels, especially on sites less windy. The performance of a wind turbine depends on three parameters: the power of wind, the power curve of the turbine and the generator's ability to respond to wind fluctuations. This paper presents a control chain conversion based on a double-fed asynchronous machine and flow-oriented. The supply system comprises of two identical converters, one connected to the rotor and the other one connected to the network via a filter. The architecture of the device is up by three commands are necessary for the operation of the turbine control extraction of maximum power of the wind to control itself (MPPT) control of the rotor side converter controlling the electromagnetic torque and stator reactive power and control of the grid side converter by controlling the DC bus voltage and active power and reactive power exchanged with the network. The proposed control has been validated in both modes of operation of the three-bladed wind 7.5 kW, using Matlab/Simulink. The results of simulation control technology study provide good dynamic performance and static.

Keywords: D.F.I.G, variable wind speed, hypersynchrone, energy quality, hyposynchrone

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Authors: Filali Kamel, Sbartai Badreddine

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The cyclic resistance curves developed by Andrus and Stokoe related to shear wave velocity case history databases are frequently used in accordance with the assumption of the Seed and Idriss simplified procedure. These cyclic resistance curves were deduced using a database according to the cyclic stress ratio (CSR) proposed by Seed and Idriss. Their approach is founded on the hypothesis that the dynamic cyclic shear stress (τd) is always less than that given by the simplified procedure (τr), as deduced by Seed and Idriss through their simplifying assumptions (rd= τd / τr <1). In 2017, Filali and Sbartai demonstrated that rd can often exceed 1, and they proposed a correction for the CSR in cases where rd > 1. Therefore, the correction of CSR implies that the cyclic resistance ratio (CRR) must also be corrected because it is defined by the boundary curve, which separates the liquefied and nonliqueified cases plotted using the original CSR of Seed and Idriss on which values of CRR are equal to CSR. For this purpose, in the context of this study, we have proposed in the range when the peak ground acceleration is ≤0.30g, which corresponds to rd>1, a modified boundary curve in accordance with the corrected version of the simplified method, which provides the safest case, generalize its use for any used earthquakes and allows the simplified method to be the more conservative.

Keywords: liquefaction, soil, earthquake, simplified method, cyclic stress ratio, cyclique resistance ratio

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Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

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Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: identification, Hammerstein-Wiener, optimization, quantization

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Authors: Lourena M. Veríssimo, Lucas A. Machado, Renata Rutckeviski, Francisco H. Xavier Júnior, Éverton N. Alencar, Andreza R. V. Morais, Teresa R. F. Dantas, Christian M. Oliveira, Arnóbio A. Silva Júnior, Eryvaldo S. T. Egito

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This study aimed to obtain emulsion systems based on bullfrog oil (BO). The BO was extracted at 80ºC and analyzed by Gas Chromatography-Mass Spectrometry (GC/MS). The critical Hydrophilic-Lipophilic Balance (HLBc) Assay of the BO was performed through BO, Tween® 20, Span® 80 and deionized water mixtures using an Ultra-Turrax® and determined using dynamic light scattering, pH, electrical conductivity and creaming rate. Then, a pseudoternary phase diagram (PPD) was constructed by water titration. The GC/MS analysis of BO suggested Methyl Oleate (9.26%) as major compound. The HLBc was 12.1, wherein the correspondent emulsion showed a pH of 4.83±1.29, electrical conductivity of 103.65 µS, creaming rate of 2.51±0.54%, droplet size of 207.07±8.31 nm and polydispersity index of 0.212±0.005. The PPD showed different formulations characterized as O/W emulsions. Thus, the PPD proved to be a useful tool to produce BO emulsions, in which their constituents may vary within the range of the desired system.

Keywords: bullfrog (Rana catesbeiana Shaw) oil, emulsion production, hydrophilic-lipophilic balance, gas chromatography/mass spectrometry analysis

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Authors: Elham Kiyani

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In this paper, we first introduce the concept of Q-efficient solutions in a real linear space not necessarily endowed with a topology, where Q is some nonempty (not necessarily convex) set. We also used the scalarization technique including the Gerstewitz function generated by a nonconvex set to characterize these Q-efficient solutions. The algebraic concepts of interior and closure are useful to study optimization problems without topology. Studying nonconvex vector optimization is valuable since topological interior is equal to algebraic interior for a convex cone. So, we use the algebraic concepts of interior and closure to define Q-weak efficient solutions and Q-Henig proper efficient solutions of set-valued optimization problems, where Q is not a convex cone. Optimization problems with set-valued maps have a wide range of applications, so it is expected that there will be a useful analytical tool in optimization theory for set-valued maps. These kind of optimization problems are closely related to stochastic programming, control theory, and economic theory. The paper focus on nonconvex problems, the results are obtained by assuming generalized non-convexity assumptions on the data of the problem. In convex problems, main mathematical tools are convex separation theorems, alternative theorems, and algebraic counterparts of some usual topological concepts, while in nonconvex problems, we need a nonconvex separation function. Thus, we consider the Gerstewitz function generated by a general set in a real linear space and re-examine its properties in the more general setting. A useful approach for solving a vector problem is to reduce it to a scalar problem. In general, scalarization means the replacement of a vector optimization problem by a suitable scalar problem which tends to be an optimization problem with a real valued objective function. The Gerstewitz function is well known and widely used in optimization as the basis of the scalarization. The essential properties of the Gerstewitz function, which are well known in the topological framework, are studied by using algebraic counterparts rather than the topological concepts of interior and closure. Therefore, properties of the Gerstewitz function, when it takes values just in a real linear space are studied, and we use it to characterize Q-efficient solutions of vector problems whose image space is not endowed with any particular topology. Therefore, we deal with a constrained vector optimization problem in a real linear space without assuming any topology, and also Q-weak efficient and Q-proper efficient solutions in the senses of Henig are defined. Moreover, by means of the Gerstewitz function, we provide some necessary and sufficient optimality conditions for set-valued vector optimization problems.

Keywords: algebraic interior, Gerstewitz function, vector closure, vector optimization

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Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

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The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

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Authors: Lo Kar Yin, Law Ka Mei

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Architectural, engineering, construction and operations (AECO) industry practitioners have been well adapting to the dynamic construction market from the fundamental training of its discipline. As further triggered by the pandemic since 2019, great steps are taken in virtual environment and the best collaboration is strived with project teams without boundaries. With adoption of Building Information Modeling-based approach and qualitative analysis, this paper is to review quantity take-off and cost estimation process through modeling techniques in liaison with suppliers, fabricators, subcontractors, contractors, designers, consultants and services providers in the construction industry value chain for automatic project cost budgeting, project cost control and cost evaluation on design options of in-situ reinforced-concrete construction and Modular Integrated Construction (MiC) at design stage, variation of works and cash flow/spending analysis at construction stage as far as practicable, with a view to sharing the findings for enhancing mutual trust and co-operation among AECO industry practitioners. It is to foster development through a common prototype of design and build project delivery method in NEC Engineering and Construction Contract (ECC) Options A and C.

Keywords: building information modeling, cost estimation, quantity take-off, modeling techniques

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Authors: Elcin Timur Cakmak, Ayse Oguzlar

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This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: T. D. Tran, H. Schlegel, R. Neugebauer

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Ball screws are an important component in machine tools. In mechatronic systems and machine tools, a ball screw has to work usually at a high speed. Otherwise the axial compliance of the ball screw, in combination with the inertia of the slide, the motor, the coupling and the screw, will cause an oscillation resonance, which limits the systems bandwidth and consequently influences performance of the motion controller. In this paper, the modal analysis method by measuring and analysing the vibrating parameters of the ball screw system to determine the dynamic characteristic of existing structures is used. On the one hand, the results of this study were obtained by the theoretical analysis and the modal testing of a ball screw system test station with the help of an impact hammer, respectively using excitation by motor. The experimental study showed oscillating forms of the ball screw for each frequency and obtained eigenfrequencies of the ball screw system. On the other hand, in this research a simulation with the help of the numerical modal analysis in order to analyse the oscillation and to find the eigenfrequencies of the ball screw system is used. Furthermore, the model order reduction by modal reduction and also according to Guyan is carried out. On the basis of these results a secure and also rapid commissioning of the control loops with regard to operating in their optimal function is targeted.

Keywords: modal analysis, ball screw, controller system, machine tools

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Authors: Eiji Okano, Kazuyuki Inagaki

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We revisit Uribe's `Fiscal Theory of Sovereign Risk' advocating that there is a trade-off between stabilizing inflation and suppressing default. We develop a class of dynamic stochastic general equilibrium (DSGE) model with nominal rigidities and compare two de facto inflation stabilization policies, optimal monetary policy and optimal monetary and fiscal policy with the minimizing interest rate spread policy which completely suppress the default. Under the optimal monetary and fiscal policy, not only the nominal interest rate but also the tax rate work to minimize welfare costs through stabilizing inflation. Under the optimal monetary both inflation and output gap are completely stabilized although those are fluctuating under the optimal monetary policy. In addition, volatility in the default rate under the optimal monetary policy is considerably lower than one under the optimal monetary policy. Thus, there is not the SI-SD trade-off. In addition, while the minimizing interest rate spread policy makes inflation rate severely volatile, the optimal monetary and fiscal policy stabilize both the inflation and the default. A trade-off between stabilizing inflation and suppressing default is not so severe what pointed out by Uribe.

Keywords: sovereign risk, optimal monetary policy, fiscal theory of the price level, DSGE

Procedia PDF Downloads 320

Authors: Rasha S. Kamal, Reham I. El-Shazly, Reem K. Farag

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Green nano-branched structural compounds were synthesized by adding 1% by weight of clay nanoparticle to different moles ratios of either dodecyl acrylate or triethylenetetramine using a simple one-pot method. The synthesized nano polymers were provided with different terminations. In order to confirm the chemical structure of the produced nanocomposites, FTIR and 1HNMR spectroscopy were performed. Additionally, Dynamic Light Scattering (DLS) analysis was used to assess the size and dispersion of the produced branching nano polymers. Using a Gel-permeation chromatograph, the molecular weights of the produced modified green nano hyperbranched polymer with various terminations were determined. the prepared nano samples with different molar feed ratios dodecyl acrylate: triethylenetetramine (DDA: TETA) was designed as An, Bn, Cn, Dn and En. Moreover, the synthesized compounds are expressed as viscosity index improvers (VII); The VI rises when prepared additive concentrations in the solution improve, as does the VI as prepared hyperbranched polymers' triethylenetetramine content rises, and the most effective VI is (E). All of the synthesized green hyperbranched nanocomposites have Newtonian rheological behavior as their rheological behavior.

Keywords: green hyperbranched polymer, DLS, viscosity index improver, Michael addition, nano clay

Procedia PDF Downloads 117