Search results for: linear programming problem

Authors: Archana Gupta, Rajesh Kumar

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The chemistry of chalcones has generated intensive scientific studies throughout the world. Especially, interest has been focused on the synthesis and biodynamic activities of chalcones. The blue light transmittance, excellent crystallizability and the two planar rings connected through a conjugated double bond show that chalcone derivatives are superior nonlinear organic compounds. 3-(2-Chloro-6-fluoro¬phen¬yl)-1-(2-thien¬yl) prop-2-en-1-one, 3-(2, 4- Dichlorophenyl) – 1 - (4-methylphenyl) – prop -2-en-1-one, (2E)-3-[4-(methylsulfanyl) phenyl]-1-(4-nitrophenyl) prop-2-en-1-one are some chalcone derivatives exhibiting non linear optical (NLO) properties. NLO materials have been extensively investigated in recent years as they are the key elements for photonic technologies of optical communication, optical interconnect oscillator, amplifier, frequency converter etc. Due to their high molecular hyperpolarizabilities, organic materials display a number of significant NLO properties. Experimental measurements and theoretical calculations on molecular hyperpolarizability β have become one of the key factors in the design of second order NLO materials. Theoretical determination of hyperpolarizability is quite useful both in understanding the relationship between the molecular structure and NLO properties. It also provides a guideline to experimentalists for the design and synthesis of organic NLO materials. Quantum-chemical calculations have made an important contribution to the understanding of the electronic polarization underlying the molecular NLO processes and the establishment of structure–property relationships. In the present investigation, the detailed vibrational analysis of some chalcone derivatives is taken up to understand the correlation of the charge transfer interaction and the NLO activity of the molecules based on density functional theory calculations. The vibrational modes contributing toward the NLO activity have been identified and analyzed. Rather large hyperpolarizability derived by theoretical calculations suggests the possible future use of these compounds for non-linear optical applications. The study suggests the importance of π - conjugated systems for non-linear optical properties and the possibility of charge transfer interactions. We hope that the results of the present study of chalcone derivatives are of assistance in development of new efficient materials for technological applications.

Keywords: hyperpolarizability, molecular structure, NLO material, quantum chemical calculations

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Authors: Navneet Kaur, S. D. Tiwari

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Superparamagnetism is an interesting phenomenon and observed in small particles of magnetic materials. It arises due to a reduction in particle size. In the superparamagnetic state, as the thermal energy overcomes magnetic anisotropy energy, the magnetic moment vector of particles flip their magnetization direction between states of minimum energy. Superparamagnetic nanoparticles have been attracting the researchers due to many applications such as information storage, magnetic resonance imaging, biomedical applications, and sensors. For information storage, thermal fluctuations lead to loss of data. So that nanoparticles should have high blocking temperature. And to achieve this, nanoparticles should have a higher magnetic moment and magnetic anisotropy constant. In this work, the magnetic anisotropy constant of the antiferromagnetic nanoparticles system is determined. Magnetic studies on nanoparticles of NiO (nickel oxide) are reported well. This antiferromagnetic nanoparticle system has high blocking temperature and magnetic anisotropy constant of order 105 J/m3. The magnetic study of NiO nanoparticles in the superparamagnetic region is presented. NiO particles of two different sizes, i.e., 6 and 8 nm, are synthesized using the chemical route. These particles are characterized by an x-ray diffractometer, transmission electron microscope, and superconducting quantum interference device magnetometry. The magnetization vs. applied magnetic field and temperature data for both samples confirm their superparamagnetic nature. The blocking temperature for 6 and 8 nm particles is found to be 200 and 172 K, respectively. Magnetization vs. applied magnetic field data of NiO is fitted to an appropriate magnetic expression using a non-linear least square fit method. The role of particle size distribution and magnetic anisotropy is taken in to account in magnetization expression. The source code is written in Python programming language. This fitting provides us the magnetic anisotropy constant for NiO and other magnetic fit parameters. The particle size distribution estimated matches well with the transmission electron micrograph. The value of magnetic anisotropy constants for 6 and 8 nm particles is found to be 1.42 X 105 and 1.20 X 105 J/m3, respectively. The obtained magnetic fit parameters are verified using the Neel model. It is concluded that the effect of magnetic anisotropy should not be ignored while studying the magnetization process of nanoparticles.

Keywords: anisotropy, superparamagnetic, nanoparticle, magnetization

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Authors: Raj Banerjee, Aniruddha Sengupta

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An earthquake event, associated with a typical fault rupture, initiates at the source, propagates through a rock or soil medium and finally daylights at a surface which might be a populous city. The detrimental effects of an earthquake are often quantified in terms of the responses of superstructures resting on the soil. Hence, there is a need for the estimation of amplification of the bedrock motions due to the influence of local site conditions. In the present study, field borehole log data of Mangalwadi and Walkeswar sites in Mumbai city are considered. The data consists of variation of SPT N-value with the depth of soil. A correlation between shear wave velocity (Vₛ) and SPT N value for various soil profiles of Mumbai city has been developed using various existing correlations which is used further for site response analysis. MATLAB program is developed for studying the ground response analysis by performing two dimensional linear and equivalent linear analysis for some of the typical Mumbai soil sites using pure shear (Multi Point Constraint) boundary condition. The model is validated in linear elastic and equivalent linear domain using the popular commercial program, DEEPSOIL. Three actual earthquake motions are selected based on their frequency contents and durations and scaled to a PGA of 0.16g for the present ground response analyses. The results are presented in terms of peak acceleration time history with depth, peak shear strain time history with depth, Fourier amplitude versus frequency, response spectrum at the surface etc. The peak ground acceleration amplification factors are found to be about 2.374, 3.239 and 2.4245 for Mangalwadi site and 3.42, 3.39, 3.83 for Walkeswar site using 1979 Imperial Valley Earthquake, 1989 Loma Gilroy Earthquake and 1987 Whitter Narrows Earthquake, respectively. In the absence of any site-specific response spectrum for the chosen sites in Mumbai, the generated spectrum at the surface may be utilized for the design of any superstructure at these locations.

Keywords: deepsoil, ground response analysis, multi point constraint, response spectrum

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Authors: Christine K. Fulmer

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Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: social work education, problem-based learning, pedagogy, experiential learning, constructivist theoretical approach

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: Haobin Zheng, Xiang Zhang, Yong Shen, Hongxin Zou

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The research focuses on mode-locked fiber lasers with a non-linear amplifying loop mirror (NALM). Although these lasers have shown potential, they still have limitations in terms of low repetition rate. The self-starting of mode-locking in NALM is influenced by the cross-phase modulation (XPM) effect, which has not been thoroughly studied. The aim of this study is two-fold. First, to overcome the difficulties associated with increasing the repetition rate in mode-locked fiber lasers with NALM. Second, to analyze the influence of XPM on self-starting of mode-locking. The power distributions of two counterpropagating beams in the NALM and the differential non-linear phase shift (NPS) accumulations are calculated. The analysis is conducted from the perspective of NPS accumulation. The differential NPSs for continuous wave (CW) light and pulses in the fiber loop are compared to understand the inverse saturable absorption (ISA) mechanism during pulse formation in NALM. The study reveals a difference in differential NPSs between CW light and pulses in the fiber loop in NALM. This difference leads to an ISA mechanism, which has not been extensively studied in artificial saturable absorbers. The ISA in NALM provides an explanation for experimentally observed phenomena, such as active mode-locking initiation through tapping the fiber or fine-tuning light polarization. These findings have important implications for optimizing the design of NALM and reducing the self-starting threshold of high-repetition-rate mode-locked fiber lasers. This study contributes to the theoretical understanding of NALM mode-locked fiber lasers by exploring the ISA mechanism and its impact on self-starting of mode-locking. The research fills a gap in the existing knowledge regarding the XPM effect in NALM and its role in pulse formation. This study provides insights into the ISA mechanism in NALM mode-locked fiber lasers and its role in selfstarting of mode-locking. The findings contribute to the optimization of NALM design and the reduction of self-starting threshold, which are essential for achieving high-repetition-rate operation in fiber lasers. Further research in this area can lead to advancements in the field of mode-locked fiber lasers with NALM.

Keywords: inverse saturable absorption, NALM, mode-locking, non-linear phase shift

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Authors: Thepnarintra Praphanphat

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The purposes of this study were to: 1) investigate operation conditions of SME automotive part industry in Bangkok and vicinity and 2) to compare operation problem levels of SME automotive part industry in Bangkok and vicinity according to the sizes of the enterprises. Samples in this study included 196 entrepreneurs of SME automotive part industry in Bangkok and vicinity derived from simple random sampling and calculation from R. V. Krejcie and D. W. Morgan’s tables. Research statistics included frequency, percentage, mean, standard deviation, and T-test. The results revealed that in general the problem levels of SME automotive part industry in Bangkok and vicinity were high. When considering in details, it was found that the problem levels were high at every aspect, i.e. personal, production, export, finance, and marketing respectively. The comparison of the problem levels according to the sizes of the enterprises revealed statistically significant differences at .05. When considering on each aspect, it was found that the aspect with the statistical difference at .05 included 5 aspects, i.e. production, marketing, finance, personal, and export. The findings also showed that small enterprises faced more severe problems than those of medium enterprises.

Keywords: automotive part industry, operation problems, SME, Perimeter

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Authors: Ahmadali Shirazytabar, Hamidreza Namazi

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The inherent irreversibility of thermo-acoustics primarily in the stack region causes poor efficiency of thermo-acoustic engines which is the major weakness of these devices. In view of the above, this study examines entropy generation in the stack of a thermo-acoustic system. For this purpose two parallel plates representative of the stack is considered. A general equation for entropy generation is derived based on the Second Law of thermodynamics. Assumptions such as Rott’s linear thermo-acoustic approximation, boundary layer type flow, etc. are made to simplify the governing continuity, momentum and energy equations to achieve analytical solutions for velocity and temperature. The entropy generation equation is also simplified based on the same assumptions and then is converted to dimensionless form by using characteristic entropy generation. A time averaged entropy generation rate followed by a global entropy generation rate are calculated and graphically represented for further analysis and inspecting the effect of different parameters on the entropy generation.

Keywords: thermo-acoustics, entropy, second law of thermodynamics, Rott’s linear thermo-acoustic approximation

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Authors: Nurbanu Guzey, S. Jagannathan

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Locating radio controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, Uniform Linear Array (ULA)

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Authors: Kedar Hardikar, Joe Varghese

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Conductive adhesives have found wide-ranging applications in electronics industry ranging from fixing a defective conductor on printed circuit board (PCB) attaching an electronic component in an assembly to protecting electronics components by the formation of “Faraday Cage.” The reliability requirements for the conductive adhesive vary widely depending on the application and expected product lifetime. While the conductive adhesive is required to maintain the structural integrity, the electrical performance of the associated sub-assembly can be affected by the degradation of conductive adhesive. The degradation of the adhesive is dependent upon the highly varied use case. The conventional approach to assess the reliability of the sub-assembly involves subjecting it to the standard environmental test conditions such as high-temperature high humidity, thermal cycling, high-temperature exposure to name a few. In order to enable projection of test data and observed failures to predict field performance, systematic development of an acceleration factor between the test conditions and field conditions is crucial. Common acceleration factor models such as Arrhenius model are based on rate kinetics and typically rely on an assumption of linear degradation in time for a given condition and test duration. The application of interest in this work involves conductive adhesive used in an electronic circuit of a capacitive sensor. The degradation of conductive adhesive in high temperature and humidity environment is quantified by the capacitance values. Under such conditions, the use of established models such as Hallberg-Peck model or Eyring Model to predict time to failure in the field typically relies on linear degradation rate. In this particular case, it is seen that the degradation is nonlinear in time and exhibits a square root t dependence. It is also shown that for the mechanism of interest, the presence of moisture is essential, and the dominant mechanism driving the degradation is the diffusion of moisture. In this work, a framework is developed to incorporate nonlinear degradation of the conductive adhesive for the development of an acceleration factor. This method can be extended to applications where nonlinearity in degradation rate can be adequately characterized in tests. It is shown that depending on the expected product lifetime, the use of conventional linear degradation approach can overestimate or underestimate the field performance. This work provides guidelines for suitability of linear degradation approximation for such varied applications

Keywords: conductive adhesives, nonlinear degradation, physics of failure, acceleration factor model.

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Authors: Rakesh Kumar, A. K. Ghosh

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The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

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Authors: Chen-Ya Juan

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In recent years, the increasing number of children with special needs has brought a lot of attention by many scholars and experts in education, which enforced the preschool teachers face the harsh challenge in the classroom. To protect the right of equal education for all children, enhance the quality of children learning, and take care of the needs of children with special needs, the special education paraprofessional becomes one of the future employment trends for students of the department of the early childhood care and education. Problem-based learning is a problem-oriented instruction, which is different from traditional instruction. The instructor first designed an ambiguous problem direction, following the basic knowledge of early intervention, students had to find clues to solve the problem defined by themselves. In the class, the total instruction included 20 hours, two hours per week. The primary purpose of this paper is to investigate the relationship of student academic scores, self-awareness, learning motivation, learning attitudes, and early intervention knowledge. A total of 105 college students participated in this study and 97 questionnaires were effective. The effective response rate was 90%. The student participants included 95 females and two males. The average age of the participants was 19 years old. The questionnaires included 125 questions divided into four major dimensions: (1) Self-awareness, (2) learning motivation, (3) learning attitudes, and (4) early intervention knowledge. The results indicated (1) the scores of self-awareness were 58%; the scores of the learning motivations was 64.9%; the scores of the learning attitudes was 55.3%. (2) After the instruction, the early intervention knowledge has been increased to 64.2% from 38.4%. (3) Student’s academic performance has positive relationship with self-awareness (p < 0.05; R = 0.506), learning motivation (p < 0.05; R = 0.487), learning attitudes (p < 0.05; R = 0.527). The results implied that although students had gained early intervention knowledge by using PBL instruction, students had medium scores on self-awareness and learning attitudes, medium high in learning motivations.

Keywords: college students, children with special needs, problem-based learning, learning motivation

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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World-wide spread of coronavirus grows the concern about planning for the excess demand of hospital services in response to COVID-19 pandemic. The surge in the hospital services demand beyond the current capacity leads to shortage of ICU beds and ventilators in some parts of US. In this study, we forecast the required number of hospital beds and possible shortage of beds in US during COVID-19 pandemic to be used in the planning and hospitalization of new cases. In this paper, we used a data on COVID-19 deaths and patients’ hospitalization besides the data on hospital capacities and utilization in US from publicly available sources and national government websites. we used a novel ensemble modelling of deep learning networks, based on stacking different linear and non-linear layers to predict the shortage in hospital beds. The results showed that our proposed approach can predict the excess hospital beds demand very well and this can be helpful in developing strategies and plans to mitigate this gap.

Keywords: COVID-19, deep learning, ensembled models, hospital capacity planning

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Authors: H. Nikzad, S. Yoshitomi

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This paper presents the design application and reinforcement detailing of 15 storied reinforced concrete shear wall-frame structure based on linear static analysis. Databases are generated for section sizes based on automated structural optimization method utilizing Active-set Algorithm in MATLAB platform. The design constraints of allowable section sizes, capacity criteria and seismic provisions for static loads, combination of gravity and lateral loads are checked and determined based on ASCE 7-10 documents and ACI 318-14 design provision. The result of this study illustrates the efficiency of proposed method, and is expected to provide a useful reference in designing of RC shear wall-frame structures.

Keywords: design constraints, ETABS, linear static analysis, MATLAB, RC shear wall-frame structures, structural optimization

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Authors: K. Farheen, A. Munir

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Seismic response of the multi-storey buildings is created by the interaction of both the structure and underlying soil medium. The seismic design philosophy is incorporated using response modification factor 'R'. Current code based values of 'R' factor does not reflect the SSI problem as it is based on fixed base condition. In this study, the modified values of 'R' factor for moment resisting frame (MRF) considering SSI are evaluated. The response of structure with and without SSI has been compared using equivalent linear static and nonlinear static pushover analyses for 10-storied moment resisting frame building. The building is located in seismic zone 2B situated on different soils with shear wave velocity (Vₛ) of 300m/sec (SD) and 1200m/s (SB). Code based 'R' factor value for building frame system has been taken as 5.5. Soil medium is modelled using identical but mutually independent horizontal and vertical springs. It was found that the modified 'R' factor values have been decreased by 47% and 43% for soil SD and SB respectively as compared to that of code based 'R' factor.

Keywords: buildings, SSI, shear wave velocity, R factor

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Authors: Abdon Choque-Rivero

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The Jacobi system with the Dirichlet boundary condition is considered on a half-line lattice when the coefficients are real valued. The inverse problem of recovery of the coefficients from various data sets containing the so-called transmission eigenvalues is analyzed. The Marchenko method is utilized to solve the corresponding inverse problem.

Keywords: inverse scattering, discrete system, transmission eigenvalues, Marchenko method

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Authors: Bahram Besharti, Hossein Navid, Hadi Karimi, Hossein Behfar, Iraj Eskandari

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Multiple or miss sowing by seed drills is a common problem on the farm. This problem causes overuse of seeds, wasting energy, rising crop treatment cost and reducing crop yield in harvesting. To be informed of mentioned faults and monitoring the performance of seed drills during sowing, developing a seed sensor for detecting seed mass flow rate and monitoring in a delivery tube is essential. In this research, an infrared seed sensor was developed to estimate seed mass flow rate in seed drills. The developed sensor comprised of a pair of spaced apart circuits one acting as an IR transmitter and the other acting as an IR receiver. Optical coverage in the sensing section was obtained by setting IR LEDs and photo-diodes directly on opposite sides. Passing seeds made interruption in radiation beams to the photo-diode which caused output voltages to change. The voltage difference of sensing units summed by a microcontroller and were converted to an analog value by DAC chip. The sensor was tested by using a roller seed metering device with three types of seeds consist of chickpea, wheat, and alfalfa (representing large, medium and fine seed, respectively). The results revealed a good fitting between voltage received from seed sensor and mass flow of seeds in the delivery tube. A linear trend line was set for three seeds collected data as a model of the mass flow of seeds. A final mass flow model was developed for various size seeds based on receiving voltages from the seed sensor, thousand seed weight and equivalent diameter of seeds. The developed infrared seed sensor, besides monitoring mass flow of seeds in field operations, can be used for the assessment of mechanical planter seed metering unit performance in the laboratory and provide an easy calibrating method for seed drills before planting in the field.

Keywords: seed flow, infrared, seed sensor, seed drills

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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Authors: Rahal Nacer, Beghdad Houda, Tehami Mohamed, Souici Abdelaziz

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Although the shrinkage of the concrete causes undesirable parasitic effects to the structure, it can then harm the resistance and the good appearance of the structure. Long term behaviourmodelling of steel-concrete composite beams requires the use of the time variable and the taking into account of all the sustained stress history of the concrete slab constituting the cross section. The work introduced in this article is a theoretical study of the behaviour of composite beams with respect to the phenomenon of concrete shrinkage. While using the theory of the linear viscoelasticity of the concrete, and on the basis of the rate of creep method, in proposing an analytical model, made up by a system of two linear differential equations, emphasizing the effects caused by shrinkage on the resistance of a steel-concrete composite beams. Results obtained from the application of the suggested model to a steel-concrete composite beam are satisfactory.

Keywords: composite beams, shrinkage, time, rate of creep method, viscoelasticity theory

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Authors: S. Athiralakshmi, B.E. Bhojaraja, U. Pruthviraj

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In agriculture, remote sensing is applied for monitoring of plant development, evaluating of physiological processes and growth conditions. Especially valuable are the spatio-temporal aspects of the remotely sensed data in detecting crop state differences and stress situations. In this study, hyperion imagery is used for classifying arecanut crops based on their age so that these maps can be used in yield estimation of crops, irrigation purposes, applying fertilizers etc. Traditional hard classifiers assigns the mixed pixels to the dominant classes. The proposed method uses a sub pixel level classifier called linear spectral unmixing available in ENVI software. It provides the relative abundance of surface materials and the context within a pixel that may be a potential solution to effectively identifying the land-cover distribution. Validation is done referring to field spectra collected using spectroradiometer and the ground control points obtained from GPS.

Keywords: FLAASH, Hyperspectral remote sensing, Linear Spectral Unmixing, Spectral Angle Mapper Classifier.

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Authors: Maryam Abata, Moulhime El Bekkali, Said Mazer, Catherine Algani, Mahmoud Mehdi

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One major problem of most electronic systems operating in the millimeter wave band is the signal generation with a high purity and a stable carrier frequency. This problem is overcome by using the combination of a signal with a low frequency local oscillator (LO) and several stages of frequency multipliers. The use of these frequency multipliers to create millimeter-wave signals is an attractive alternative to direct generation signal. Therefore, the isolation problem of the local oscillator from the other stages is always present, which leads to have various mechanisms that can disturb the oscillator performance, thus a buffer amplifier is often included in oscillator outputs. In this paper, we present the study and design of a buffer amplifier in the mm-wave band using a 0.15μm pHEMT from UMS foundry. This amplifier will be used as a part of a frequency quadrupler at 60 GHz.

Keywords: Mm-wave band, local oscillator, frequency quadrupler, buffer amplifier

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Authors: Purva Joshi, Rohit Thanki, Omar Hanif

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Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

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Authors: Salinee Thumronglaohapun

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The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.

Keywords: location-allocation problem, stochastic demand, local search, genetic algorithm

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Authors: Hesham Shaalan

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Senior design projects teach students many important skills. One of the major goals is to prepare students to apply effective problem-solving techniques to a problem that represents a real-world situation. This includes the ability to define the problem, compare alternative solutions, identify the best solution, and design the system. This paper describes the design of a shipboard power plant as a senior project in the Marine Engineering program at the U.S. Merchant Marine Academy. The design project was supervised by faculty members who guided a multidisciplinary group of seniors. The research project was sponsored by the Office of Naval Research. Each group of seniors focused on one of the main design aspects of the project, including the electric power system, nuclear power plant, ship hull design, and economics.

Keywords: senior design project, shipboard power system, engineering education, marine engineering

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Authors: Ling Dai

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Surface-sensing devices such as atomic force microscope have been widely used to characterize the surface structure and properties of nanoscale polymer films. However, using molecular dynamics simulations, we show that there is intrinsic and unavoidable inelastic deformation at polymer surfaces induced by the sensing tip. For linear chain polymers like perfluoropolyether, such tip-induced deformation derives from the differences in the atomic interactions which are atomic specie-based Van der Waals interactions, and resulting in atomic shuffling and causing inelastic alternation in both molecular structures and mechanical properties at the regions of the polymer surface. For those aromatic chain polymers like epoxy, the intrinsic deformation is depicted as the intra-chain rotation of aromatic rings and kinking of linear atomic connections. The present work highlights the need to reinterpret the data obtained from surface-sensing tests by considering this intrinsic inelastic deformation occurring at polymer surfaces.

Keywords: polymer, surface, nano, molecular dynamics

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Authors: Abdulkerim Ilgun, Ahmad Javid Zia

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In developing countries, the urban populations are increasing rapidly and with this increment the residential areas are experiencing major problems. Construction of high-rise buildings in confined spaces is one of the most practical solutions for this problem. However, by living in high-rise buildings and sharing common residential areas, residents will face many problems. Irritating sound problem which is known as noise is one of the major problems mentioned above. The second most important problem is the weight of the high-rise buildings which makes the structure more vulnerable to earthquakes. To decrease earthquake loads it’s very important to decrease the weight of the buildings. To solve the problem of noise and keep the building weight at minimum level, experimentally designed soundproof gypsum partition wall which has optimum thickness has been used in high-rise story building and the results have been compared with ordinary brick partition walls. In this compression the effect of weights of soundproof gypsum walls and ordinary brick walls in accordance to structural engineering have been investigated.

Keywords: cellubor, gypsum board, gypsum partition walls, light partition walls, noise, sound

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Authors: Nicole Vlasman, Karamjeet Dhillon

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Over the past four years, the Healthy Relationships Program has been delivered in community organizations and schools across Canada. More than 240 groups have been facilitated in collaboration with 33 organizations. As a result, 2157 youth have been engaged in the programming. The purpose and scope of the Healthy Relationships Program are to offer sustainable, evidence-based skills through small group implementation to prevent violence and promote positive, healthy relationships in youth. The program development has included extensive networking at regional and national levels. The Healthy Relationships Program is currently being implemented, adapted, and researched within the Resilience and Inclusion through Strengthening and Enhancing Relationships (RISE-R) project. Alongside the project’s research objectives, the RISE-R team has worked to virtually share the ongoing findings of the project through a slow ontology approach. Slow ontology is a practice integrated into project systems and structures whereby slowing the pace and volume of outputs offers creative opportunities. Creative production reveals different layers of success and complements the project, the building blocks for sustainability. As a result of integrating a slow ontology approach, the RISE-R team has developed a Geographic Information System (GIS) that documents local landscapes through a Story Map feature, and more specifically, video installations. Video installations capture the cartography of space and place within the context of singular diverse community spaces (case studies). By documenting spaces via human connections, the project captures narratives, which further enhance the voices and faces of the community within the larger project scope. This GIS project aims to create a visual and interactive flow of information that complements the project's mixed-method research approach. Conclusively, creative project development in the form of a geographic information system can provide learning and engagement opportunities at many levels (i.e., within community organizations and educational spaces or with the general public). In each of these disconnected spaces, fragmented stories are connected through a visual display of project outputs. A slow ontology practice within the context of the RISE-R project documents activities on the fringes and within internal structures; primarily through documenting project successes as further contributions to the Centre for School Mental Health framework (philosophy, recruitment techniques, allocation of resources and time, and a shared commitment to evidence-based products).

Keywords: community programming, geographic information system, project development, project management, qualitative, slow ontology

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Authors: K. N. Kiran, S. Anish

Abstract:

It is well known that secondary flow loses account about one third of the total loss in any axial turbine. Modern gas turbine height is smaller and have longer chord length, which might lead to increase in secondary flow. In order to improve the efficiency of the turbine, it is important to understand the behavior of secondary flow and device mechanisms to curtail these losses. The objective of the present work is to understand the effect of a stream wise end-wall fence on the aerodynamics of a linear turbine cascade. The study is carried out computationally by using commercial software ANSYS CFX. The effect of end-wall on the flow field are calculated based on RANS simulation by using SST transition turbulence model. Durham cascade which is similar to high-pressure axial flow turbine for simulation is used. The aim of fencing in blade passage is to get the maximum benefit from flow deviation and destroying the passage vortex in terms of loss reduction. It is observed that, for the present analysis, fence in the blade passage helps reducing the strength of horseshoe vortex and is capable of restraining the flow along the blade passage. Fence in the blade passage helps in reducing the under turning by 7⁰ in comparison with base case. Fence on end-wall is effective in preventing the movement of pressure side leg of horseshoe vortex and helps in breaking the passage vortex. Computations are carried for different fence height whose curvature is different from the blade camber. The optimum fence geometry and location reduces the loss coefficient by 15.6% in comparison with base case.

Keywords: boundary layer fence, horseshoe vortex, linear cascade, passage vortex, secondary flow

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

Abstract:

In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Mohand Kessal, Rachid Boucetta, Mourad Tikobaini, Mohammed Zamoum

Abstract:

Leakage problem of two-component fluids flow is modeled for a transient one-dimensional homogeneous bubbly flow and developed by taking into account the effect of a leak located at the middle point of the pipeline. The corresponding three conservation equations are numerically resolved by an improved characteristic method. The obtained results are explained and commented in terms of physical impact on the flow parameters.

Keywords: fluid transients, pipelines leaks, method of characteristics, leakage problem

Procedia PDF Downloads 467