Search results for: linear analysis

Authors: Hamed Khani Arani, Mohammad Shariyat, Armaghan Mohammadian

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In the present study, the free vibration of magnetostrictive nano-plate (MsNP) resting on the Pasternak foundation is investigated. Firstly, the modified couple stress (MCS) and nonlocal elasticity theories are compared together and taken into account to consider the small scale effects; in this paper not only two theories are analyzed but also it improves the MCS theory is more accurate than nonlocal elasticity theory in such problems. A feedback control system is utilized to investigate the effects of a magnetic field. First-order shear deformation theory (FSDT), Hamilton’s principle and energy method are utilized in order to drive the equations of motion and these equations are solved by differential quadrature method (DQM) for simply supported boundary conditions. The MsNP undergoes in-plane forces in x and y directions. In this regard, the dimensionless frequency is plotted to study the effects of small scale parameter, magnetic field, aspect ratio, thickness ratio and compression and tension loads. Results indicate that these parameters play a key role on the natural frequency. According to the above results, MsNP can be used in the communications equipment, smart control vibration of nanostructure especially in sensor and actuators such as wireless linear micro motor and smart nano valves in injectors.

Keywords: feedback control system, magnetostrictive nano-plate, modified couple stress theory, nonlocal elasticity theory, vibration analysis

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Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao

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Three preceramic polymer formulations for potential use in 3D printing technologies were investigated. The polymeric precursors include an allyl hydrido polycarbosilane (SMP-10), SMP-10/1,6-dexanediol diacrylate (HDDA) mixture, and polydimethylsiloxane (PDMS). The rheological property of the polymeric precursors, including the viscosity within a wide shear rate range was compared to determine the applicability in additive manufacturing technology. The structural properties of the polymeric solutions and their photocureability were investigated using Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC). Moreover, thermogravimetric analysis (TGA) and X-ray diffraction (XRD) were utilized to study polymeric to ceramic conversion for versatile precursors. The prepared precursor resin proved to have outstanding photo-curing properties and the ability to transform to the silicon carbide phase at temperatures as low as 850 °C. The obtained ceramic was fully dense with nearly linear shrinkage and a shiny, smooth surface after pyrolysis. Furthermore, after pyrolysis to 1350 °C and TGA analysis, PDMS polymer showed the highest onset decomposition temperature and the lowest retained weight (52 wt%), while SMP.10/HDDA showed the lowest onset temperature and ceramic yield (71.7 wt%). In terms of crystallography, the ceramic matrix composite appeared to have three coexisting phases, including silicon carbide, and silicon oxycarbide. The results are very promising to fabricate ceramic materials working at high temperatures with complex geometries.

Keywords: preceramic polymer, silicon carbide, photocuring, allyl hydrido polycarbosilane, SMP-10

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: B. G. Abiona, A. A. Onaseso, T. D. Odetayo, J. Yila, O. E. Fapojuwo, K. G. Adeosun

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This study determines the perceived effects of work-family balance on employees’ job satisfaction among Extension Agents in the Agricultural Development Programme (ADP) in southwest Nigeria. A multistage sampling technique was used to select 256 respondents for the study. Data on personal characteristics, work-family balance domain, and job satisfaction were collected. The collected data were analysed using descriptive statistics, Chi-square, Pearson Product Moment Correlation (PPMC), multiple linear regression, and Student T-test. Results revealed that the mean age of the respondents was 40 years; the majority (59.3%) of the respondents were male, and slightly above half (51.6%) of the respondents had MSc as their highest academic qualification. Findings revealed that turnover intention (x ̅ = 3.20) and work-role conflict (x ̅ = 3.06) were the major perceived work-family balance domain in the studied areas. Further, the result showed that the respondents have a high (79%) level of job satisfaction. Multiple linear regression revealed that job involvement (ß=0.167, p<0.01) and work-role conflict (ß= -0.221, p<0.05) contributed significantly to employees’ level of job satisfaction. The results of the Student T-test revealed a significant difference in the perceived work-family balance domain (t = 0.43, p<0.05) between the two studied areas. The study concluded that work-role conflict among employees causes work-family imbalance and, therefore, negatively affects employees’ job satisfaction. The definition of job design among the respondents that will create a balance between work and family is highly recommended.

Keywords: work-life, conflict, job satisfaction, extension agent

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Authors: Y. M. Aiyesimi, G. T. Okedayo, O. W. Lawal

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The analysis has been carried out to study unsteady MHD thin film flow of a third grade fluid down an inclined plane with heat transfer when the slippage between the surface of plane and the lower surface of the fluid is valid. The governing nonlinear partial differential equations involved are reduced to linear partial differential equations using regular perturbation method. The resulting equations were solved analytically using method of separation of variable and eigenfunctions expansion. The solutions obtained were examined and discussed graphically. It is interesting to find that the variation of the velocity and temperature profile with the slip and magnetic field parameter depends on time.

Keywords: non-Newtonian fluid, MHD flow, thin film flow, third grade fluid, slip boundary condition, heat transfer, separation of variable, eigenfunction expansion

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Authors: Milica Ž. Karadžić, Lidija R. Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Z. Kovačević, Anamarija I. Mandić, Katarina Penov-Gaši, Andrea R. Nikolić, Aleksandar M. Oklješa

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This study considered selection of the in silico molecular descriptors and the models for newly synthesized steroid derivatives description and their characterization using chemometric techniques. Multiple linear regression (MLR) models were established and gave the best molecular descriptors for quantitative structure-retention relationship (QSRR) modeling of the retention of the investigated molecules. MLR models were without multicollinearity among the selected molecular descriptors according to the variance inflation factor (VIF) values. Used molecular descriptors were ranked using generalized pair correlation method (GPCM). In this method, the significant difference between independent variables can be noticed regardless almost equal correlation between dependent variable. Generated MLR models were statistically and cross-validated and the best models were kept. Models were ranked using sum of ranking differences (SRD) method. According to this method, the most consistent QSRR model can be found and similarity or dissimilarity between the models could be noticed. In this study, SRD was performed using average values of experimentally observed data as a golden standard. Chemometric analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their potential biological activity and further synthesis. This article is based upon work from COST Action (CM1105), supported by COST (European Cooperation in Science and Technology).

Keywords: generalized pair correlation method, molecular descriptors, regression analysis, steroids, sum of ranking differences

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Authors: Yasmine Abu Adla, Racha Soubra, Milana Kasab, Mohamad O. Diab, Aly Chkeir

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Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

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Authors: Abdullah Bajelan, Adel Akbarimajd

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Object manipulation techniques in robotics can be categorized in two major groups including manipulation with grasp and manipulation without grasp. The original aim of this paper is to develop an object manipulation method where in addition to being grasp-less, the manipulation task is done in a passive approach. In this method, linear and angular positions of the object are changed and its manipulation path is controlled. The manipulation path is a helix track with constant radius and incline. The method presented in this paper proposes a system which has not the actuator and the active controller. So this system requires a passive mechanical intelligence to convey the object from the status of the source along the specified path to the goal state. This intelligent is created based on utilizing the geometry of the system components. A general set up for the components of the system is considered to satisfy the required conditions. Then after kinematical analysis, detailed dimensions and geometry of the mechanism is obtained. The kinematical results are verified by simulation in ADAMS.

Keywords: mechanical intelligence, object manipulation, passive mechanism, passive non-prehensile manipulation

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Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

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Authors: Ethan Petersen

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In this paper, we analyze the volatility of Apple’s stock beginning January 3, 2005 up to October 9, 2014, then focus on a range from 30 days prior to each product announcement until 30 days after. Product announcements are filtered; announcements whose 60 day range is devoid of other events are separated. This filtration is chosen to isolate, and study, a potential cross-effect. Concerning Apple keynotes, there are two significant dates: the day the invitations to the event are received and the day of the event itself. As such, the statistical analysis is conducted for both invite-centered and event-centered time frames. A comparison to the VIX is made to determine if the trend is simply following the market or deviating. Regardless of the filtration, we find that there is a clear deviation from the market. Comparing these data sets, there are significantly different trends: isolated events have a constantly decreasing, erratic trend in volatility but an increasing, linear trend is observed for clustered events. According to the Efficient Market Hypothesis, we would expect a change when new information is publicly known and the results of this study support this claim.

Keywords: efficient market hypothesis, event study, volatility, VIX

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Authors: Sanaz Ahmadzadeh Siyahrood, Arghavan Ebrahimi, Mohammadjavad Mahdavinejad

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Islamic culture was accountable for a plethora of development in astronomy and science in the medieval term, and in geometry likewise. Geometric patterns are reputable in a considerable number of cultures, but in the Islamic culture the patterns have specific features that connect the Islamic faith to mathematics. In Islamic art, three fundamental shapes are generated from the circle shape: triangle, square and hexagon. Originating from their quiddity, each of these geometric shapes has its own specific structure. Even though the geometric patterns were generated from such simple forms as the circle and the square, they can be combined, duplicated, interlaced, and arranged in intricate combinations. So in order to explain geometrical interaction principles between square and equal triangle, in the first definition step, all types of their linear forces individually and in the second step, between them, would be illustrated. In this analysis, some angles will be created from intersection of their directions. All angles are categorized to some groups and the mathematical expressions among them are analyzed. Since the most geometric patterns in Islamic art and architecture are based on the repetition of a single motif, the evaluation results which are obtained from a small portion, is attributable to a large-scale domain while the development of infinitely repeating patterns can represent the unchanging laws. Geometric ornamentation in Islamic art offers the possibility of infinite growth and can accommodate the incorporation of other types of architectural layout as well, so the logic and mathematical relationships which have been obtained from this analysis are applicable in designing some architecture layers and developing the plan design.

Keywords: angle, equal triangle, square, structural hierarchy

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Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

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The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

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Authors: Hossein Tavallali, Mohammad Ali Karimi, Gohar Deilamy-Rad

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The proposed method for speciation, preconcentration and determination of Fe(II) and Fe(III) in pharmaceutical products was developed using of alumina-coated magnetite nanoparticles (Fe₃O₄/Al₂O₃ NPs) as solid phase extraction (SPE) sorbent in magnetic mixed hemimicell solid phase extraction (MMHSPE) technique followed by flame atomic absorption spectrometry analysis. The procedure is based on complexation of Fe(II) with 1, 10-phenanthroline (OP) as complexing reagent for Fe(II) that immobilized on the modified Fe₃O₄/Al₂O₃ NPs. The extraction and concentration process for pharmaceutical sample was carried out in a single step by mixing the extraction solvent, magnetic adsorbents under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. Fe(III) ions determined after facility reduced to Fe(II) by added a proper reduction agent to sample solutions. Compared with traditional methods, the MMHSPE method simplified the operation procedure and reduced the analysis time. Various influencing parameters on the speciation and preconcentration of trace iron, such as pH, sample volume, amount of sorbent, type and concentration of eluent, were studied. Under the optimized operating conditions, the preconcentration factor of the modified nano magnetite for Fe(II) 167 sample was obtained. The detection limits and linear range of this method for iron were 1.0 and 9.0 - 175 ng.mL⁻¹, respectively. Also the relative standard deviation for five replicate determinations of 30.00 ng.mL^-1 Fe²⁺ was 2.3%.

Keywords: Alumina-Coated magnetite nanoparticles, Magnetic Mixed Hemimicell Solid-Phase Extraction, Fe(ΙΙ) and Fe(ΙΙΙ), pharmaceutical sample

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Authors: Mohammadreza Akbari, Sara Akbari, Davood Domiri Ganji, Pooya Solimani, Reza Khalili

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In this paper, three complicated nonlinear differential equations(PDE,ODE) in the field of engineering and non-vibration have been analyzed and solved completely by new method that we have named it Akbari-Ganji's Method (AGM) . As regards the previous published papers, investigating this kind of equations is a very hard task to do and the obtained solution is not accurate and reliable. This issue will be emerged after comparing the achieved solutions by Numerical Method. Based on the comparisons which have been made between the gained solutions by AGM and Numerical Method (Runge-Kutta 4th), it is possible to indicate that AGM can be successfully applied for various differential equations particularly for difficult ones. Furthermore, It is necessary to mention that a summary of the excellence of this method in comparison with the other approaches can be considered as follows: It is noteworthy that these results have been indicated that this approach is very effective and easy therefore it can be applied for other kinds of nonlinear equations, And also the reasons of selecting the mentioned method for solving differential equations in a wide variety of fields not only in vibrations but also in different fields of sciences such as fluid mechanics, solid mechanics, chemical engineering, etc. Therefore, a solution with high precision will be acquired. With regard to the afore-mentioned explanations, the process of solving nonlinear equation(s) will be very easy and convenient in comparison with the other methods. And also one of the important position that is explored in this paper is: Trigonometric and exponential terms in the differential equation (the method AGM) , is no need to use Taylor series Expansion to enhance the precision of the result.

Keywords: new method (AGM), complex non-linear partial differential equations, damping ratio, energy lost per cycle

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Authors: Amir M. Shikhli, Refaat H. Abdel-Razek, Salaheddine Bendak

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Innovation is considered to be one of the key factors that influence long-term success of any company. The problem of many organizations in developing countries is trying to implement innovation without a strong basis within the organizational culture to support it. The objective of this study is to assess the effects of organizational culture on innovation in one of the biggest information technology organizations in UAE, Injazat Data System. First, an Organizational Culture Assessment Instrument (OCAI) was used as a survey and Competing Value Framework as a model to analyze the existing culture within the organization and determine its characteristics. Following that, a modified version of the Community Innovation Survey (CIS) was used to determine innovation types introduced by the organization. Then multiple linear regression analysis was used to find out the effects of existing organizational culture on innovation. Results show that existing organizational culture is composed of a combination of Hierarchy (29.4%), Clan (25.8%), Market (24.9%) and Adhocracy (19.9%). Results of the second survey show that the organization focuses on organizational innovation (26.8%) followed by market and product innovations (25.6%) and finally process innovation (22.0%). Regression analysis results reveal that for each innovation type there is a recommended combination of the four culture types. For product innovation, the combination is 47.4% Clan, 17.9% Adhocracy, 1.0% Market and 33.3% Hierarchy; for process innovation it is 19.7% Clan, 45.2% Adhocracy, 32.0% Market and 3.1% Hierarchy; for organizational innovation the combination is 5.4% Clan, 32.7% Adhocracy, 6.0% Market and 55.9% Hierarchy; and for market innovation it is 25.5% Clan, 42.6% Adhocracy, 32.6% Market and 8.4% Hierarchy. Based on these recommended combinations, this study suggests two ways to enhance the innovation culture in the organization. First, if the management decides on the innovation type to be enhanced, a comparison between the existing culture and the recommended combination of selected innovation types will lead to difference in percentages of each culture type. Then further analysis should show how to modify the existing culture to match the recommended combination. Second, if the innovation type is not selected, but the management wants to enhance innovation culture in the organization, the difference in percentages of each culture type will lead to finding out the recommended combination of culture types that gives the narrowest gap between existing culture and recommended combination.

Keywords: developing countries, organizational culture, innovation types, product innovation, process innovation, organizational innovation, marketing innovation

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Authors: Md. S. Ansari, S. S. Motsa

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In this paper, an analysis has been made on the flow of non-Newtonian viscoelastic nanofluid over a linearly stretching sheet under the influence of uniform magnetic field. Heat transfer characteristics is analyzed taking into the effect of nonlinear radiation and non-uniform heat source/sink. Transport equations contain the simultaneous effects of Brownian motion and thermophoretic diffusion of nanoparticles. The relevant partial differential equations are non-dimensionalized and transformed into ordinary differential equations by using appropriate similarity transformations. The transformed, highly nonlinear, ordinary differential equations are solved by spectral local linearisation method. The numerical convergence, error and stability analysis of iteration schemes are presented. The effects of different controlling parameters, namely, radiation, space and temperature-dependent heat source/sink, Brownian motion, thermophoresis, viscoelastic, Lewis number and the magnetic force parameter on the flow field, heat transfer characteristics and nanoparticles concentration are examined. The present investigation has many industrial and engineering applications in the fields of coatings and suspensions, cooling of metallic plates, oils and grease, paper production, coal water or coal–oil slurries, heat exchangers’ technology, and materials’ processing and exploiting.

Keywords: magnetic field, nonlinear radiation, non-uniform heat source/sink, similar solution, spectral local linearisation method, Rosseland diffusion approximation

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Authors: Sharib Ahmed, Mansoor Rafi, Kamran Ali Awan, Faraz Khaskhali, Amir Maqbool, Altaf Hashmi

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Medical linear accelerators (LINAC’s) used in radiotherapy treatments produce undesired neutrons when they are operated at energies above 8 MeV, both in electron and photon configuration. Neutrons are produced by high-energy photons and electrons through electronuclear (e, n) a photonuclear giant dipole resonance (GDR) reactions. These reactions occurs when incoming photon or electron incident through the various materials of target, flattening filter, collimators, and other shielding components in LINAC’s structure. These neutrons may reach directly to the patient, or they may interact with the surrounding materials until they become thermalized. A work has been set up to study the effect of different parameter on the production of neutron around the room by photonuclear reactions induced by photons above ~8 MeV. One of the commercial available neutron detector (Ludlum Model 42-31H Neutron Detector) is used for the detection of thermal and fast neutrons (0.025 eV to approximately 12 MeV) inside and outside of the treatment room. Measurements were performed for different field sizes at 100 cm source to surface distance (SSD) of detector, at different distances from the isocenter and at the place of primary and secondary walls. Other measurements were performed at door and treatment console for the potential radiation safety concerns of the therapists who must walk in and out of the room for the treatments. Exposures have taken place from Elekta Synergy® linear accelerators for two different energies (10 MV and 18 MV) for a given 200 MU’s and dose rate of 600 MU per minute. Results indicates that neutron doses at 100 cm SSD depend on accelerator characteristics means jaw settings as jaws are made of high atomic number material so provides significant interaction of photons to produce neutrons, while doses at the place of larger distance from isocenter are strongly influenced by the treatment room geometry and backscattering from the walls cause a greater doses as compare to dose at 100 cm distance from isocenter. In the treatment room the ambient dose equivalent due to photons produced during decay of activation nuclei varies from 4.22 mSv.h−1 to 13.2 mSv.h−1 (at isocenter),6.21 mSv.h−1 to 29.2 mSv.h−1 (primary wall) and 8.73 mSv.h−1 to 37.2 mSv.h−1 (secondary wall) for 10 and 18 MV respectively. The ambient dose equivalent for neutrons at door is 5 μSv.h−1 to 2 μSv.h−1 while at treatment console room it is 2 μSv.h−1 to 0 μSv.h−1 for 10 and 18 MV respectively which shows that a 2 m thick and 5m longer concrete maze provides sufficient shielding for neutron at door as well as at treatment console for 10 and 18 MV photons.

Keywords: equivalent doses, neutron contamination, neutron detector, photon energy

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Authors: Birhanu Betela Warssamo

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Background: There is limited evidence on the prevalence and risk factors for hepatitis C virus (HCV) infection among waste handlers in the Sidama region, Ethiopia; however, this knowledge is necessary for the effective prevention of HCV infection in the region. Methods: A cross-sectional study was conducted among randomly selected waste collectors from October 2021 to 30 July 2022 in different public hospitals in the Sidama region of Ethiopia. Serum samples were collected from participants and screened for anti-HCV using a rapid immunochromatography assay. Socio-demographic and risk factor information of waste handlers was gathered by pretested and well-structured questionnaires. The generalized linear model (GLM) was conducted using R software, and P-value < 0.05 was declared statistically significant. Results: From a total of 282 participating waste handlers, 16 (5.7%) (95% CI, 4.2 – 8.7) were infected with the hepatitis C virus. The educational status of waste handlers was the significant demographic variable that was associated with the hepatitis C virus (AOR = 0.055; 95% CI = 0.012 – 0.248; P = 0.000). More married waste handlers, 12 (75%), were HCV positive than unmarried, 4 (25%) and married waste handlers were 2.051 times (OR = 2.051, 95%CI = 0.644 –6.527, P = 0.295) more prone to HCV infection, compared to unmarried, which was statistically insignificant. The GLM showed that exposure to blood (OR = 8.26; 95% CI = 1.878–10.925; P = 0.037), multiple sexual partners (AOR = 3.63; 95% CI = 2.751–5.808; P = 0.001), sharp injury (AOR = 2.77; 95% CI = 2.327–3.173; P = 0.036), not using PPE (AOR = 0.77; 95% CI = 0.032–0.937; P = 0.001), contact with jaundiced patient (AOR = 3.65; 95% CI = 1.093–4.368; P = 0 .0048) and unprotected sex (AOR = 11.91; 95% CI = 5.847–16.854; P = 0.001) remained statistically significantly associated with HCV positivity. Conclusions: The study revealed that there was a high prevalence of hepatitis C virus infection among waste handlers in the Sidama region, Ethiopia. This demonstrated that there is an urgent need to increase preventative efforts and strategic policy orientations to control the spread of the hepatitis C virus.

Keywords: Hepatitis C virus, risk factors, waste handlers, prevalence, Sidama Ethiopia

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Authors: Ram Mohan, Richard Haney, Ajit Kelkar

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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

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Authors: B. B. Siswanto, A. Halimi, K. M. H. J. Tandayu, C. Abdillah, F. Nanda , E. Chandra

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Nowadays, modern cardiac biomarkers, such as ST2 and NT-proBNP, have important roles in predicting morbidity and mortality in heart failure patients. Abnormalities of serum electrolytes, sepsis or infection, and deteriorating renal function will worsen the conditions of patients with heart failure. It is intriguing to know whether cardiac biomarkers elevations are affected by laboratory findings in heart failure patients. We recruited 65 patients from the heart failure clinic in NCVC Harapan Kita in 2014-2015. All of them have consented for laboratory examination, including cardiac biomarkers. The findings were recorded in our Research and Development Centre and analyzed using linear regression to find whether there is a relationship between laboratory findings (sodium, potassium, creatinine, and leukocytes) and ST2 or NT-proBNP. From 65 patients, 26.9% of them are female, and 73.1% are male, 69.4% patients classified as NYHA I-II and 31.6% as NYHA III-IV. The mean age is 55.7+11.4 years old; mean sodium level is 136.1+6.5 mmol/l; mean potassium level is 4.7+1.9 mmol/l; mean leukocyte count is 9184.7+3622.4 /ul; mean creatinine level is 1.2+0.5 mg/dl. From linear regression logistics, the relationship between NT-proBNP and sodium level (p<0.001), as well as leukocyte count (p=0.002) are significant, while NT-proBNP and potassium level (p=0.05), as well as creatinine level (p=0.534) are not significant. The relationship between ST2 and sodium level (p=0.501), potassium level (p=0.76), leukocyte level (p=0.897), and creatinine level (p=0.817) are not significant. To conclude, laboratory findings are more sensitive in predicting NT-proBNP elevation than ST2 elevation. Larger studies are needed to prove that NT-proBNP correlation with laboratory findings is more superior than ST2.

Keywords: heart failure, laboratory, NT-proBNP, ST2

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Authors: Layla El Gaini, Majdouline Belaqziz, Meriem Outaki, Mariam Minhaj

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In this study, it introduce and validate a high-performance liquid chromatography method with diode-array detection (HPLC-DAD) specifically designed for the accurate quantification of caffeic acid in phenolic extracts obtained from olive mill wastewater. The separation process of caffeic acid was effectively achieved through the use of an Acclaim Polar Advantage column (5µm, 250x4.6mm). A meticulous multi-step gradient mobile phase was employed, comprising water acidified with phosphoric acid (pH 2.3) and acetonitrile, to ensure optimal separation. The diode-array detection was adeptly conducted within the UV–VIS spectrum, spanning a range of 200–800 nm, which facilitated precise analytical results. The method underwent comprehensive validation, addressing several essential analytical parameters, including specificity, repeatability, linearity, as well as the limits of detection and quantification, alongside measurement uncertainty. The generated linear standard curves displayed high correlation coefficients, underscoring the method's efficacy and consistency. This validated approach is not only robust but also demonstrates exceptional reliability for the focused analysis of caffeic acid within the intricate matrices of wastewater, thus offering significant potential for applications in environmental and analytical chemistry.

Keywords: high-performance liquid chromatography (HPLC-DAD), caffeic acid analysis, olive mill wastewater phenolics, analytical method validation

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Nazanin Amanat, Alison Tayler, Steve Whyard

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While chemical insecticides effectively control many insect pests, they also harm many non-target species. Double-stranded RNA (dsRNA) pesticides, in contrast, can be designed to target unique gene sequences and thus act in a species-specific manner. DsRNA insecticides do not, however, work equally well for all insects, and for some species that are considered refractory to dsRNA, a primary factor affecting efficacy is the relative ease by which dsRNA can enter a target cell’s cytoplasm. In this study, we are examining how different structured dsRNAs (linear, hairpin, and paperclip) can enter mosquito and lepidopteran cells, as they represent dsRNA-sensitive and refractory species, respectively. To determine how the dsRNAs enter the cells, we are using chemical inhibitors and RNA interference (RNAi)-mediated knockdown of key proteins associated with different endocytosis processes. Understanding how different dsRNAs enter cells will ultimately help in the design of molecules that overcome refractoriness to RNAi or develop resistance to dsRNA-based insecticides. To date, we have conducted chemical inhibitor experiments on both cell lines and have evidence that linear dsRNAs enter the cells using clathrin-mediated endocytosis, while the paperclip dsRNAs (pcRNAs) can enter both species’ cells in a clathrin-independent manner to induce RNAi. An alternative uptake mechanism for the pcRNAs has been tentatively identified, and the outcomes of our RNAi-mediated knockdown experiments, which should provide corroborative evidence of our initial findings, will be discussed.

Keywords: dsRNA, RNAi, uptake, insecticides, dipteran, lepidopteran

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Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

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Authors: Seyedeh Rozhano Azimi Hashemi

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There is no doubt that ‘Art’ is a social phenomena and cinema is the most social kind of art. Hence, it’s clear that we can analyze the relation’s of cinema and art from different aspects. In this paper sociological cinema will be investigated which, is a subdivision of sociological art. This term will be discussed by two main approaches. One of these approaches is focused on the effects of cinema on the society, which is known as “Effects Theory” and the second one, which is dealing with the reflection of social issues in cinema is called ” Reflection Theory”. "Reflect theory" approach, unlike "Effects theory" is considering movies as documents, in which social life is reflected, and by analyzing them, the changes and tendencies of a society are understood. Criticizing these approaches to cinema and society doesn’t mean that they are not real. Conversely, it proves the fact that for better understanding of cinema and society’s relation, more complicated models are required, which should consider two aspects. First, they should be bilinear and they should provide a dynamic and active relation between cinema and society, as for the current concept social life and cinema have bi-linear effects on each other, and that’s how they fit in a dialectic and dynamic process. Second, it should pay attention to the role of inductor elements such as small social institutions, marketing, advertisements, cultural pattern, art’s genres and popular cinema in society. In the current study, image of middle class in cinema of Iran and changing the role of women in cinema and society which were two bold issue that cinema and society faced since 1979 revolution till 80s are analyzed. Films as an artwork on one hand, are reflections of social changes and with their effects on the society on the other hand, are trying to speed up the trends of these changes. Cinema by the illustration of changes in ideologies and approaches in exaggerated ways and through it’s normalizing functions, is preparing the audiences and public opinions for the acceptance of these changes. Consequently, audience takes effect from this process, which is a bi-linear and interactive process.

Keywords: Iranian Cinema, Cinema and Society, Middle Class, Woman’s Role

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Authors: L. Tonia, I. Daglis, W. Kurth

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The sound of the universe creates an affinity with the sounds of music. The analysis of the sound of space focuses on the existence of a tone material, the microstructure and macrostructure, and the form of the sound through the signals recorded during the flight of the spacecraft Van Allen Probes and Cassini’s mission. The sound becomes from the frequencies that belong to electromagnetic waves. Plasma Wave Science Instrument and Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) recorded the signals from space. A transformation of that signals to audio gave the opportunity to study and analyze the sound. Due to the fact that the musical tone pitch has a frequency and every electromagnetic wave produces a frequency too, the creation of a musical score, which appears as the sound of space, can give information about the form, the symmetry, and the harmony of the sound. The conversion of space radio emissions to audio provides a number of tone pitches corresponding to the original frequencies. Through the process of these sounds, we have the opportunity to present a music score that “composed” from space. In this score, we can see some basic features associated with the music form, the structure, the tone center of music material, the construction and deconstruction of the sound. The structure, which was built through a harmonic world, includes tone centers, major and minor scales, sequences of chords, and types of cadences. The form of the sound represents the symmetry of a spiral movement not only in micro-structural but also to macro-structural shape. Multiple glissando sounds in linear and polyphonic process of the sound, founded in magnetic fields around Earth, Saturn, and Jupiter, but also a spiral movement appeared on the spectrogram of the sound. Whistles, Auroral Kilometric Radiations, and Chorus emissions reveal movements similar to musical excerpts of works by contemporary composers like Sofia Gubaidulina, Iannis Xenakis, EinojuhamiRautavara.

Keywords: space sound analysis, spiral, space music, analysis

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Aleksandra Tepic-Horecki, Zdravko Sumic

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In this paper, the influence of six different phytochemical content (phenols, carotenoids, chlorophyll a, chlorophyll b, chlorophyll a + b and vitamin C) on antioxidant potential of Murai and Levistro lettuce varieties was evaluated. Variable selection was made by generalized pair correlation method (GPCM) as a novel ranking method. This method is used for the discrimination between two variables that almost equal correlate to a dependent variable. Fisher’s conditional exact and McNemar’s test were carried out. Established multiple linear (MLR) models were statistically evaluated. As the best phytochemicals for the antioxidant potential prediction, chlorophyll a, chlorophyll a + b and total carotenoids content stand out. This was confirmed through both GPCM and MLR, predictive ability of obtained MLR can be used for antioxidant potential estimation for similar lettuce samples. This article is based upon work from the project of the Provincial Secretariat for Science and Technological Development of Vojvodina (No. 114-451-347/2015-02).

Keywords: antioxidant activity, generalized pair correlation method, lettuce, regression analysis

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Authors: Rym Ghariani, Younes Boujelbene

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This study aimed to examine the impact of digitalization and supply chain integration on the financial performance of companies in the agro-industrial sector in Tunisia, highlighting the growing importance of digital technologies in modern economies. The results were analyzed using a questionnaire and using principal component analysis, as well as linear regression modeling with SPSS26. The results demonstrate that the digitalization and integration of the supply chain have a significant impact on the financial results of Tunisian agro-industrial companies. In theory, this study provides a better understanding of the effects of digital advancements and supply chain strategies on financial results in this specific area. This study, therefore, studies the relationship between these variables and financial efficiency, highlighting the significant impacts of these technological and strategic elements on the financial results of agro-industrial companies in Tunisia.

Keywords: digitalization, supply chain integration, financial performance, Tunisian agro-industrial sector

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Authors: M. C. Yu, Z. L. Niu, L. G. Zhang, W. W. Cui, Y. L. Zhang

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According to the theory of the vibration isolation for linear systems, linear damping can reduce the transmissibility at the resonant frequency, but inescapably increase the transmissibility of the isolation frequency region. To resolve this problem, nonlinear vibration isolation technology has recently received increasing attentions. Shear thickening fluid (STF) is a special colloidal material. When STF is subject to high shear rate, it rheological property changes from a flowable behavior into a rigid behavior, i.e., it presents shear thickening effect. STF isolator is a vibration isolator using STF as working material. Because of shear thickening effect, STF isolator is a variable-damped isolator. It exhibits small damping under high vibration frequency and strong damping at resonance frequency due to shearing rate increasing. So its special inherent character is very favorable for vibration isolation, especially for restraining resonance. In this paper, firstly, STF was prepared by dispersing nano-particles of silica into polyethylene glycol 200 fluid, followed by rheological properties test. After that, an STF isolator was designed. The vibration isolation system supported by STF isolator was modeled, and the numerical simulation was conducted to study the vibration isolation properties of STF. And finally, the effect factors on vibrations isolation performance was also researched quantitatively. The research suggests that owing to its variable damping, STF vibration isolator can effetely restrain resonance without bringing unfavorable effect at high frequency, which meets the need of ideal damping properties and resolves the problem of traditional isolators.

Keywords: shear thickening fluid, variable-damped isolator, vibration isolation, restrain resonance

Procedia PDF Downloads 181