Search results for: small signal model

Authors: Nikhil Yadav, Shubham Verma

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Gas lift is a common technique used to optimize oil production in wells. Prosper software is a powerful tool for modeling and optimizing gas lift systems in oil wells. This review paper examines the effectiveness of Prosper software in optimizing gas lift systems in oil-producing wells. The literature review identified several studies that demonstrated the use of Prosper software to adjust injection rate, depth, and valve characteristics to optimize gas lift system performance. The results showed that Prosper software can significantly improve production rates and reduce operating costs in oil-producing wells. However, the accuracy of the model depends on the accuracy of the input data, and the cost of Prosper software can be high. Therefore, further research is needed to improve the accuracy of the model and evaluate the cost-effectiveness of using Prosper software in gas lift system optimization

Keywords: gas lift, prosper software, injection rate, operating costs, oil-producing wells

Procedia PDF Downloads 64

Authors: Leonel Lipa Cusi, Enrique Nestor Pasquel Carbajal, Laura Marina Navarro Alvarado, José Del Álamo Carazas

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This research analyses the accuracy of the ultrasound and the pulse echo ultrasound technic to find voids and to measure thickness of concrete elements. These mentioned air voids are simulated by polystyrene expanded and hollow containers of thin thickness made of plastic or cardboard of different sizes and shapes. These targets are distributed strategically inside concrete at different depths. For this research, a shear wave pulse echo ultrasonic device of 50 KHz is used to scan the concrete elements. Despite the small measurements of the concrete elements and because of voids’ size are near the half of the wavelength, pre and post processing steps like voltage, gain, SAFT, envelope and time compensation were made in order to improve imaging results.

Keywords: ultrasonic, concrete, thickness, pulse echo, void

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Authors: Fatemeh Asadi Farsad, Sima Modirkhameneh

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The purpose of this study was to explore the pattern of Psychological Well-Being (PWB) of Iranian male and female EFL teachers during the pandemic. It was intended to see if such a drastic change in the context and mode of teaching affects teachers' PWB. Furthermore, the possible difference between the six elements of PWB of Iranian EFL male vs. female teachers during the pandemic was investigated. The other purpose was to find out the EFL teachers’ perceptions of any modifications, and factors leading to such modifications in their PWB during pandemic. For the purpose of this investigation, a total of 81 EFL teachers (59 female, 22 male) with an age range of 25 to 35 were conveniently sampled from different cities in Iran. Ryff’s PWB questionnaire was sent to participant teachers through online platforms to elicit data on their PWB. As for their perceptions on the possible modifications and the factors involved in PWB during pandemic, a set of semi-structured interviews were run among both sample groups. The findings revealed that male EFL teachers had the highest mean on personal growth, followed by purpose of life, and self-acceptance and the lowest mean on environmental mastery. With a slightly similar pattern, female EFL teachers had the highest mean on personal growth, followed by purpose in life, and positive relationship with others with the lowest mean on environmental mastery. However, no significant difference was observed between the male and female groups’ overall means on elements of PWB. Additionally, participants perceived that their anxiety level in online classes altered due to factors like (1) Computer literacy skills, (2) Lack of social communications and interactions with colleagues and students, (3) Online class management, (4) Overwhelming workloads, and (5) Time management. The study ends with further suggestions as regards effective online teaching preparation considering teachers PWB, especially at severe situations such as covid-19 pandemic. The findings offer to determine the reformations of educational policies concerning enhancing EFL teachers’ PWB through computer literacy courses and stress management courses. It is also suggested that to proactively support teachers’ mental health, it is necessary to provide them with advisors and psychologists if possible for free. Limitations: One limitation is the small number of participants (81), suggesting that future replications should include more participants for reliable findings. Another limitation is the gender imbalance, which future studies should address to yield better outcomes. Furthermore, Limited data gathering tools suggest using observations, diaries, and narratives for more insights in future studies. The study focused on one model of PWB, calling for further research on other models in the literature. Considering the wide effect of the COVID-19 pandemic, future studies should consider additional variables (e.g., teaching experience, age, income) to understand Iranian EFL teachers’ vulnerabilities and strengths better.

Keywords: online teaching, psychological well-being, female and male EFL teachers, pandemic

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Authors: Bawadi M. A., Abbad J. A., Baras E. A.

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This study was conducted to assess wind energy resources in the area of Al-Adwas Ras-Huwirah Hadhramout Governorate, Yemen, through using statistical calculations, the Weibull model and SPSS program were used in the monthly and the annual to analyze the wind energy resource; the convergence of wind energy; turbine efficiency in the selected area. Wind speed data was obtained from NASA over a period of ten years (2010-2019) and at heights of 50 m above ground level. Probability distributions derived from wind data and their distribution parameters are determined. The density probability function is fitted to the measured probability distributions on an annual basis. This study also involves locating preliminary sites for wind farms using Geographic Information System (GIS) technology. This further leads to maximizing the output energy from the most suitable wind turbines in the proposed site.

Keywords: wind speed analysis, Yemen wind energy, wind power density, Weibull distribution model

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Authors: Min Wei

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Objectives: Experience tourism represents an advanced stage of tourism compared with sightseeing tourism and relaxation tourism. Experience tourism reflects the full respect of experience economy to the human natures. This paper chose one of the most popular ocean tourism products in Zhoushan, as a subject and investigated the constructive elements in tourist experience based on the needs of tourists. Methods: This paper started with the influences of tourism product innovation on tourist experience, then proposed a model of the relationship between tourist experience, tourist satisfaction, and the following behavior of tourists, and concluded that tourist experience improves tourist satisfaction and thereby enhances tourist loyalty based on the developmental pathway of experience tourism. To ensure the accuracy of the collected data of the research results, the sample of this questionnaire survey is chosen by the method of occasional sampling, combined with the judgment of the investigators and the convenience of the questionnaire survey, the survey objects are selected from the scenic spots of Putuo Mountain, Zhujiajian, Taohua Island, waiting room of passenger terminal, etc. Before filling in the questionnaire, the author and the respondents have a short communication. On the premise that the respondents can fully understand the purpose and content of the questionnaire, tourists fill in the questionnaire independently and collect it on the spot. Results: The research results of this paper are mainly embodied in the following aspects: it is concluded that there are many constructive factors of tourists' experience in Zhoushan tourism products. Based on Zhoushan tourism products, this paper explores the constructive factors of tourists' experience in Zhoushan tourism products from three aspects: attracting object experience, facility experience and service experience. At present, there are still big differences between Zhoushan tourism products, tourists’ expectations and tourists' experience, mainly in the aspects of transportation, publicity and tour guide service. Corresponding measures should be taken to improve tourists' experience quality and satisfaction. Conclusions: The influence factors of island tourism products are discriminated, and established a structural model of tourist experience, which includes three basic elements: attractions, facilities, and services. This model was further verified by questionnaires and analyses in Putuo Shan, Zhujia Jian, and Taohua Island. Finally, we combined this model and made some suggestions on boost the satisfaction of Zhoushan islands.

Keywords: experience tourism, tourists’ expectations, tourists' experience, tourism products

Procedia PDF Downloads 116

Authors: Anny Zambrano, German Gonzalez, Yair Quintero

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The continuum damage concept is used to study the interaction between hydraulic fractures and natural fractures, the objective is representing the path and relation among this two fractures types and predict its complex behavior without the need to pre-define their direction as occurs in other finite element applications, providing results more consistent with the physical behavior of the phenomenon. The approach uses finite element simulations through Abaqus software to model damage fracturing, the fracturing process by damage propagation in a rock. The modeling the phenomenon develops in two dimensional (2D) so that the fracture will be represented by a line and the crack front by a point. It considers nonlinear constitutive behavior, finite strain, time-dependent deformation, complex boundary conditions, strain hardening and softening, and strain based damage evolution in compression and tension. The complete governing equations are provided and the method is described in detail to permit readers to replicate all results. The model is compared to models that are published and available. Comparisons are focused in five interactions between natural fractures (NF) and hydraulic fractures: Fractured arrested at NF, crossing NF with or without offset, branching at intersecting NFs, branching at end of NF and NF dilation due to shear slippage. The most significant new finding is, that is not necessary to use pre-defined addresses propagation and stress condition can be evaluated as a dominant factor in the process. This is important because it can model in a more real way the generated complex hydraulic fractures, and be a valuable tool to predict potential problems and different geometries of the fracture network in the process of fracturing due to fluid injection.

Keywords: continuum damage, hydraulic fractures, natural fractures, complex fracture network, stiffness

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Authors: Kveta Olsanova, Gina Cook, Marija Zlatic

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This paper discusses the theoretical framework suggesting the dependencies between luxury brands’ CSR (Corporate Social Responsibility) variables and the purchase intention of luxury shoppers. The framework is based on a literature review and in-depth individual interviews with a sample of luxury users and buyers. The measures of the model are based on existing research and the authors' qualitative research results. The model suggests that purchase intention in the luxury segment is dependent on the luxury values (symbolic, experiential, functional and social), individual sustainable dimension (composed of societal, environmental and economic variables) and awareness of the brand’s CSR, the last two relationships being potentially moderated by certain conditions such as demographics and general attitudes towards CSR and sustainability. The model’s output is in the formulation of several hypotheses, to be tested in an upcoming quantitative study. The qualitative phase indicated that the perceived symbolic, functional and experiential value dimensions of luxury brands were stronger drivers of purchase intention compared to the sustainable dimension. The contribution of the research consists of highlighting CSR’s impact on customer purchase intent as a potential implication for luxury brand management due to two aspects: (i) consumer awareness of the existing CSR activities of luxury brands is low, and this might be challenged by the demands of Gen Z entrants into the lux industry as they are known for their positive approach to CSR; (ii) the UN’s SDGs will bring CSR to the attention of all industries, including currently 'CSR silent' segments represented by luxury. Our research should contribute to incorporation of strategic CSR into the policies and strategies of the luxury segment by providing evidence that luxury customers do care.

Keywords: CSR, luxury shoppers, purchase intention, sustainability

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Authors: Rong Yuan, Zhao Tao

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Only a handful of literature have used to non-linear model to investigate the influencing factors of greenhouse gas (GHG) emissions in China’s manufacturing sectors. And there is a limit in investigating quantitatively and systematically the mechanism of correlation between economic development and GHG emissions considering inherent differences among manufacturing sub-sectors. Considering the sectorial characteristics, the manufacturing sub-sectors with various impacts of output on GHG emissions may be explained by different development modes in each manufacturing sub-sector, such as investment scale, technology level and the level of international competition. In order to assess the environmental impact associated with any specific level of economic development and explore the factors that affect GHG emissions in China’s manufacturing industry during the process of economic growth, using the threshold Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, this paper investigated the influence impacts of GHG emissions for China’s manufacturing sectors of different stages of economic development. A data set from 28 manufacturing sectors covering an 18-year period was used. Results demonstrate that output per capita and investment scale contribute to increasing GHG emissions while energy efficiency, R&D intensity and FDI mitigate GHG emissions. Results also verify the nonlinear effect of output per capita on emissions as: (1) the Environmental Kuznets Curve (EKC) hypothesis is supported when threshold point RMB 31.19 million is surpassed; (2) the driving strength of output per capita on GHG emissions becomes stronger as increasing investment scale; (3) the threshold exists for energy efficiency with the positive coefficient first and negative coefficient later; (4) the coefficient of output per capita on GHG emissions decreases as R&D intensity increases. (5) FDI shows a reduction in elasticity when the threshold is compassed.

Keywords: China, GHG emissions, manufacturing industry, threshold STIRPAT model

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Authors: O. Maklouf, Ahmed Abdulla

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A general decline in the cost, size, and power requirements of electronics is accelerating the adoption of integrated GPS/INS technologies in consumer applications such Land Vehicle Navigation. Researchers are looking for ways to eliminate additional components from product designs. One possibility is to drop one or more of the relatively expensive gyroscopes from microelectromechanical system (MEMS) versions of inertial measurement units (IMUs). For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a simplified integration algorithm for strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of the low-cost IMU and because of the relatively small area of the trajectory.

Keywords: GPS, ParIMU, INS, Kalman filter

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Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

Procedia PDF Downloads 252

Authors: M. Ashaque Meah, Md. Fazlul Karim, M. Shah Noor, Nazmun Nahar Papri, M. Khalid Hossen, M. Ismoen

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Tsunami and inundation modelling due to far field tsunami propagation in a limited area is a very challenging numerical task because it involves many aspects such as the formation of various types of waves and the irregularities of coastal boundaries. To compute the effect of far field tsunami and extent of inland inundation due to far field tsunami along the coastal belts of west coast of Malaysia and Southern Thailand, a formulated boundary condition and a moving boundary condition are simultaneously used. In this study, a boundary fitted curvilinear grid system is used in order to incorporate the coastal and island boundaries accurately as the boundaries of the model domain are curvilinear in nature and the bending is high. The tsunami response of the event 26 December 2004 along the west open boundary of the model domain is computed to simulate the effect of far field tsunami. Based on the data of the tsunami source at the west open boundary of the model domain, a boundary condition is formulated and applied to simulate the tsunami response along the coastal and island boundaries. During the simulation process, a moving boundary condition is initiated instead of fixed vertical seaside wall. The extent of inland inundation and tsunami propagation pattern are computed. Some comparisons are carried out to test the validation of the simultaneous use of the two boundary conditions. All simulations show excellent agreement with the data of observation.

Keywords: open boundary condition, moving boundary condition, boundary-fitted curvilinear grids, far-field tsunami, shallow water equations, tsunami source, Indonesian tsunami of 2004

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Authors: Yumeng Ma, Fang Wang, Jinxia Huang

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Researchers put forward higher requirements for efficient acquisition and utilization of domain knowledge in the big data era. As literature is an effective way for researchers to quickly and accurately understand the research situation in their field, the knowledge discovery based on literature has become a new research method. As a tool to organize and manage knowledge in a specific domain, the subject knowledge base can be used to mine and present the knowledge behind the literature to meet the users' personalized needs. This study designs the construction route of the subject knowledge base for specific research problems. Information extraction method based on knowledge engineering is adopted. Firstly, the subject knowledge model is built through the abstraction of the research elements. Then under the guidance of the knowledge model, extraction rules of knowledge points are compiled to analyze, extract and correlate entities, relations, and attributes in literature. Finally, a database platform based on this structured knowledge is developed that can provide a variety of services such as knowledge retrieval, knowledge browsing, knowledge q&a, and visualization correlation. Taking the construction practices in the field of activating blood circulation and removing stasis as an example, this study analyzes how to construct subject knowledge base based on literature knowledge extraction. As the system functional test shows, this subject knowledge base can realize the expected service scenarios such as a quick query of knowledge, related discovery of knowledge and literature, knowledge organization. As this study enables subject knowledge base to help researchers locate and acquire deep domain knowledge quickly and accurately, it provides a transformation mode of knowledge resource construction and personalized precision knowledge services in the data-intensive research environment.

Keywords: knowledge model, literature knowledge extraction, precision knowledge services, subject knowledge base

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Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

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Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

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Authors: Ch. Sandeep Kumar Subudhi, S. Sivanandam

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Our system is to monitor the human body temperature, blood pressure (BP), Pulse Rate and ECG and tracking the patient location. In our system the body temperature is detected by using LM35 temperature sensor, blood pressure is detected by the BP sensor, pulse rate is detected by the ear plug pulse sensor and the ECG is detected by the three lead ECG sensor in the working environment of the patient. The sensed information is sent to the PIC16F877 microcontroller through signal conditioning circuit. A desired amount of sensor value is set and if it is exceeded preliminary steps should be taken by indication by buzzer. The sensor information will be transmitted from the patient unit to the main controller unit with the help of Zigbee communication medium which is connected with the microcontrollers in the both units. The main controller unit will send those sensor data as well as the location of that patient by the help of GPS module to the observer/doctor. The observer/doctor can receive the SMS sent by GSM module and further decision can be taken. The message is sent to a cell phone using global system mobile (GSM) Modem. MAX232 acts as a driver between microcontroller and modem.

Keywords: LM35, heart beat sensor, ECG Sensor, BP Sensor, Zigbee module, GSM module, GPS module, PIC16F877A microcontroller

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Authors: Kari Huhtala, Iiro Jussila

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The supervisory board is assumed to use power in the governance of a firm, but the actual use of power has been scantly investigated. The research question of the paper is “How does the supervisory board use power in the selection of the board of directors”. The data stem from 11 large Finnish agricultural cooperatives. The research approach was qualitative including semi-structured interviews of the board of directors and supervisory board chairpersons. The results were analyzed and interpreted against theories of social power. As a result, the use of power is approached from two perspectives: (1) formal position-based authority and (2) informal power. Central elements of power were the mandate of the supervisory board, the role of the supervisory board, the supervisory board chair, the nomination committee, collaboration between the supervisory board and the board of directors, the role of regions and the role of the board of directors. The study contributes to the academic discussion on corporate governance in cooperatives and on the supervisory board in the context of the two-tier model. Additional research of the model in other countries and of other types of cooperatives would further academic understanding of supervisory boards.

Keywords: board, co-operative, supervisory board, selection, director

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Authors: Aigul Manapova

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We consider an optimal control problem in the higher coefficient of nonlinear equations with a divergent elliptic operator and unbounded nonlinearity, and the Dirichlet boundary condition. The conditions imposed on the coefficients of the state equation are assumed to hold only in a small neighborhood of the exact solution to the original problem. This assumption suggests that the state equation involves nonlinearities of unlimited growth and considerably expands the class of admissible functions as solutions of the state equation. We obtain formulas for the first partial derivatives of the objective functional with respect to the control functions. To calculate the gradients the numerical solutions of the state and adjoint problems are used. We also prove that the gradient of the cost function is Lipchitz continuous.

Keywords: cost functional, differentiability, divergent elliptic operator, optimal control, unbounded nonlinearity

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Authors: Saad M. Alshehri, Tansir Ahamad

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Thiourea-Formaldehyde Pre-Polymer (TUF) was prepared by the reaction thiourea and formaldehyde in basic medium and used as a coating materials for magnetite Fe3O4. The synthesized polymer coated microspheres (TUF@Fe3O4) was characterized using FTIR, TGA SEM and TEM. Its BET surface area was up to 1680 m2 g_1. The adsorption capacity of this ACF product was evaluated in its adsorption of Methylene Blue (MB) in water under different pH values and different temperature. We found that the adsorption process was well described both by the Langmuir and Freundlich isotherm model. The kinetic processes of MB adsorption onto TUF@Fe3O4 were described in order to provide a more clear interpretation of the adsorption rate and uptake mechanism. The overall kinetic data was acceptably explained by a pseudo second-order rate model. Evaluated ∆Go and ∆Ho specify the spontaneous and exothermic nature of the reaction. The adsorption takes place with a decrease in entropy (∆So is negative). The monolayer capacity for MB was up to 450 mg g_1 and was one of the highest among similar polymeric products. It was due to its large BET surface area.

Keywords: TGA, FTIR, magentite, thiourea formaldehyde resin, methylene blue, adsorption

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Authors: Redouane Lombarkia

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To apply a new material model developed and validated for plain weave fabric CFRP composites usually used in stanchions in sub-cargo section in aircrafts. This work deals with the development of a numerical model of the fuselage section of commercial aircraft based on the pure explicit finite element method FEM within Abaqus/Explicit commercial code. The aim of this work is the evaluation of the energy absorption capabilities of a full-scale composite fuselage section, including sub-cargo stanchions, Drop tests were carried out from a free fall height of about 5 m and impact velocity of about 6 m∕s. To asses, the prediction efficiency of the proposed numerical modeling procedure, a comparison with literature existed experimental results was performed. We demonstrate the efficiency of the proposed methodology to well capture crash damage mechanisms compared to experimental results

Keywords: crashworthiness, fuselage section, finite elements method (FEM), stanchions, specific energy absorption SEA

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Authors: Haifeng Zhou, Tsungyang Liow, Xiaoguang Tu, Eujin Lim, Chao Li, Junfeng Song, Xianshu Luo, Ying Huang, Lianxi Jia, Lianwee Luo, Kim Dowon, Qing Fang, Mingbin Yu, Guoqiang Lo

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Several Germanium photodetectors (PD) built on silicon micro-disks are fabricated on the standard Si photonics multiple project wafers (MPW) and demonstrated to exhibit very low dark current, satisfactory operation bandwidth and moderate responsivity. Among them, a vertical p-i-n Ge PD based on a 2.0 µm-radius micro-disk has a dark current of as low as 35 nA, compared to a conventional PD current of 1 µA with an area of 100 µm2. The operation bandwidth is around 15 GHz at a reverse bias of 1V. The responsivity is about 0.6 A/W. Microdisk is a striking planar structure in integrated optics to enhance light-matter interaction and construct various photonics devices. The disk geometries feature in strongly and circularly confining light into an ultra-small volume in the form of whispering gallery modes. A laser may benefit from a microdisk in which a single mode overlaps the gain materials both spatially and spectrally. Compared to microrings, micro-disk removes the inner boundaries to enable even better compactness, which also makes it very suitable for some scenarios that electrical connections are needed. For example, an ultra-low power (≈ fJ) athermal Si modulator has been demonstrated with a bit rate of 25Gbit/s by confining both photons and electrically-driven carriers into a microscale volume.In this work, we study Si-based PDs with Ge selectively grown on a microdisk with the radius of a few microns. The unique feature of using microdisk for Ge photodetector is that mode selection is not important. In the applications of laser or other passive optical components, microdisk must be designed very carefully to excite the fundamental mode in a microdisk in that essentially the microdisk usually supports many higher order modes in the radial directions. However, for detector applications, this is not an issue because the local light absorption is mode insensitive. Light power carried by all modes are expected to be converted into photo-current. Another benefit of using microdisk is that the power circulation inside avoids any introduction of the reflector. A complete simulation model with all involved materials taken into account is established to study the promise of microdisk structures for photodetector by using finite difference time domain (FDTD) method. By viewing from the current preliminary data, the directions to further improve the device performance are also discussed.

Keywords: integrated optical devices, silicon photonics, micro-resonator, photodetectors

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Authors: Ngoc Nguyen

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There is large plantation of Eucalyptus globulus established which has been grown to produce pulpwood. This resource is not suitable for the production of decorative products, principally due to low grades of wood and “dull” appearance but many trials have been already undertaken for the production of veneer and veneer-based engineered wood products, such as plywood and laminated veneer lumber (LVL). The manufacture of veneer-based products has been recently identified as an unprecedented opportunity to promote higher value utilisation of plantation resources. However, many uncertainties remain regarding the impacts of inferior wood quality of young plantation trees on product recovery and value, and with respect to optimal processing techniques. Moreover, the quality of veneer and veneer-based products is far from optimal as trees are young and have small diameters; and the veneers have the significant colour variation which affects to the added value of final products. Developing production methods which would enhance appearance of low-quality veneer would provide a great potential for the production of high-value wood products such as furniture, joinery, flooring and other appearance products. One of the methods of enhancing appearance of low quality veneer, developed in Italy, involves the production of multilaminar veneer, also named “reconstructed veneer”. An important stage of the multilaminar production is colouring the veneer which can be achieved by dyeing veneer with dyes of different colours depending on the type of appearance products, their design and market demand. Although veneer dyeing technology has been well advanced in Italy, it has been focused on poplar veneer from plantation which wood is characterized by low density, even colour, small amount of defects and high permeability. Conversely, the majority of plantation eucalypts have medium to high density, have a lot of defects, uneven colour and low permeability. Therefore, detailed study is required to develop dyeing methods suitable for colouring eucalypt veneers. Brown reactive dye is used for veneer colouring process. Veneers from sapwood and heartwood of two moisture content levels are used to conduct colouring experiments: green veneer and veneer dried to 12% MC. Prior to dyeing, all samples are treated. Both soaking (dipping) and vacuum pressure methods are used in the study to compare the results and select most efficient method for veneer dyeing. To date, the results of colour measurements by CIELAB colour system showed significant differences in the colour of the undyed veneers produced from heartwood part. The colour became moderately darker with increasing of Sodium chloride, compared to control samples according to the colour measurements. It is difficult to conclude a suitable dye solution used in the experiments at this stage as the variables such as dye concentration, dyeing temperature or dyeing time have not been done. The dye will be used with and without UV absorbent after all trials are completed using optimal parameters in colouring veneers.

Keywords: Eucalyptus globulus, veneer colouring/dyeing, multilaminar veneer, reactive dye

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Authors: Kambiz Rasoulkhani, Jeanne Cole, Sybil Sharvelle, Ali Mostafavi

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Dual water distribution systems have been proposed as solutions to enhance the sustainability and resilience of urban water systems by improving performance and decreasing energy consumption. The objective of this study was to evaluate the long-term resilience and robustness of dual water distribution systems versus singular water distribution systems under various stressors such as demand fluctuation, aging infrastructure, and funding constraints. To this end, the long-term dynamics of these infrastructure systems was captured using a simulation model that integrates institutional agency decision-making processes with physical infrastructure degradation to evaluate the long-term transformation of water infrastructure. A set of model parameters that varies for dual and singular distribution infrastructure based on the system attributes, such as pipes length and material, energy intensity, water demand, water price, average pressure and flow rate, as well as operational expenditures, were considered and input in the simulation model. Accordingly, the model was used to simulate various scenarios of demand changes, funding levels, water price growth, and renewal strategies. The long-term resilience and robustness of each distribution infrastructure were evaluated based on various performance measures including network average condition, break frequency, network leakage, and energy use. An ecologically-based resilience approach was used to examine regime shifts and tipping points in the long-term performance of the systems under different stressors. Also, Classification and Regression Tree analysis was adopted to assess the robustness of each system under various scenarios. Using data from the City of Fort Collins, the long-term resilience and robustness of the dual and singular water distribution systems were evaluated over a 100-year analysis horizon for various scenarios. The results of the analysis enabled: (i) comparison between dual and singular water distribution systems in terms of long-term performance, resilience, and robustness; (ii) identification of renewal strategies and decision factors that enhance the long-term resiliency and robustness of dual and singular water distribution systems under different stressors.

Keywords: complex systems, dual water distribution systems, long-term resilience performance, multi-agent modeling, sustainable and resilient water systems

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Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

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To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

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Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: Bandreddy Anand Babu, Srinivasa Rao Mandadi, C. Pradeep Reddy, N. Ramesh Babu

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In this paper quickly illustrate the correlation investigation of Auto-Regressive Integrated Moving and Average (ARIMA) and daptive Network Based Fuzzy Inference System (ANFIS) models done by climate estimating. The climate determining is taken from University of Waterloo. The information is taken as Relative Humidity, Ambient Air Temperature, Barometric Pressure and Wind Direction utilized within this paper. The paper is carried out by analyzing the exhibitions are seen by demonstrating of ARIMA and ANIFIS model like with Sum of average of errors. Versatile Network Based Fuzzy Inference System (ANFIS) demonstrating is carried out by Mat lab programming and Auto-Regressive Integrated Moving and Average (ARIMA) displaying is produced by utilizing XLSTAT programming. ANFIS is carried out in Fuzzy Logic Toolbox in Mat Lab programming.

Keywords: ARIMA, ANFIS, fuzzy surmising tool stash, weather forecasting, MATLAB

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Jonali Baruah, Keesha Green

Abstract:

This experimental study examines the effects of anonymity in video meeting groups across the stages of innovation (idea generation, selection, and refinement) on various measures of creativity. A sample of 92 undergraduate students participated in small groups of three to four members to complete creativity, decision-making, and idea-refinement task in either anonymous or identified conditions. The study followed two anonymity (anonymous and identified) X 3 stages of innovation (idea generation, idea selection, and idea refinement) in a mixed factorial design. Results revealed that the anonymous groups produced ideas of the highest average quality in the refinement phase of innovation. The results of this study enhanced our understanding of the productivity and creativity of groups in computer-mediated communication.

Keywords: creativity, anonymity, idea-generation, idea-refinement, innovation

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

Abstract:

This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: M. N. Hanina, M. Hairul Shahril, I. Ismatul Nurul Asyikin, A. K. Abdul Jalil, M. R. Salina, M. R. Maryam, M. Rosfarizan

Abstract:

The extracellular proteins secreted by bacteria may be increased in stressful surroundings, such as in the presence of antibiotics. It appears that many antibiotics, when used at low concentrations, have in common the ability to activate or repress gene transcription, which is distinct from their inhibitory effect. There have been comparatively few studies on the potential of antibiotics as a specific chemical signal that can trigger a variety of biological functions. Therefore, this study was carried out to determine the effect of Streptomycin Sulfate in regulating extracellular proteins secreted by Bacillus subtilis ATCC21332. Results of Microdilution assay showed that the Minimum Inhibition Concentration (MIC) of Streptomycin Sulfate on B. subtilis ATCC21332 was 2.5 mg/ml. The bacteria cells were then exposed to Streptomycin Sulfate at concentration of 0.01 MIC before being further incubated for 48h to 72 h. The extracellular proteins secreted were then isolated and analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Proteins profile revealed that three additional bands with approximate sizes of 30 kDa, 22 kDa and 23 kDa were appeared for the treated bacteria with Streptomycin Sulfate. Thus, B. subtilis ATCC21332 in stressful condition with the presence of Streptomycin Sulfate at low concentration could induce the extracellular proteins secretion.

Keywords: Bacillus subtilis ATCC21332, streptomycin sulfate, extracellular proteins, antibiotics

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Authors: Lule Basha, Eralda Gjika

Abstract:

This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine-learning methods, such as random forest, are used to predict cereal yield responses to climacteric and other variables. Random Forest showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the Random Forest method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods.

Keywords: cereal yield, climate change, machine learning, multiple regression model, random forest

Procedia PDF Downloads 75