Search results for: multi linear regression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9412

Search results for: multi linear regression

8302 Digitalization, Supply Chain Integration and Financial Performance: Case of Tunisian Agro-industrial Sector

Authors: Rym Ghariani, Younes Boujelbene

Abstract:

In contemporary times, global technological advancements, particularly those in the realm of digital technology, have emerged as pivotal instruments for enterprises in fostering viable partnerships and forging meaningful alliances with other firms. The advent of these digital innovations is poised to revolutionize nearly every facet and operation within corporate entities. The primary objective of this study is to explore the correlation between digitization, integration of supply chains, and the financial efficacy of the agro-industrial sector in Tunisia. To accomplish this, data collection employed a questionnaire as the primary research instrument. Subsequently, the research queries were addressed, and hypotheses were examined by subjecting the gathered data to principal component analysis and linear regression modeling, facilitated by the utilization of SPSS26 software. The findings revealed that digitalization within the supply chain, along with external supply chain integration, exerted discernible impacts on the financial performance of the organization.

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

Procedia PDF Downloads 22
8301 Sum Capacity with Regularized Channel Inversion in Multi-Antenna Downlink Systems under Equal Power Constraint

Authors: Attaullah Khawaja, Amna Shabbir

Abstract:

Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper regularized channel inversion under equal power constraint in the multiuser multiple input multiple output (MU-MIMO) broadcast channels has been considered. Sum capacity with plain channel inversion also known as Zero Forcing Beam Forming (ZFBF) and optimum sum capacity using Dirty Paper Coding (DPC) has also been investigated. Analysis and simulations show that regularization enhances the system performance and empower linear growth in Sum Capacity and specially work well at low signal to noise ratio (SNRs) regime.

Keywords: broadcast channel, channel inversion, multiple antenna multiple-user wireless, multiple-input multiple-output (MIMO), regularization, dirty paper coding (DPC), sum capacity

Procedia PDF Downloads 512
8300 A Combined Error Control with Forward Euler Method for Dynamical Systems

Authors: R. Vigneswaran, S. Thilakanathan

Abstract:

Variable time-stepping algorithms for solving dynamical systems performed poorly for long time computations which pass close to a fixed point. To overcome this difficulty, several authors considered phase space error controls for numerical simulation of dynamical systems. In one generalized phase space error control, a step-size selection scheme was proposed, which allows this error control to be incorporated into the standard adaptive algorithm as an extra constraint at negligible extra computational cost. For this generalized error control, it was already analyzed the forward Euler method applied to the linear system whose coefficient matrix has real and negative eigenvalues. In this paper, this result was extended to the linear system whose coefficient matrix has complex eigenvalues with negative real parts. Some theoretical results were obtained and numerical experiments were carried out to support the theoretical results.

Keywords: adaptivity, fixed point, long time simulations, stability, linear system

Procedia PDF Downloads 300
8299 A Linear Programming Approach to Assist Roster Construction Under a Salary Cap

Authors: Alex Contarino

Abstract:

Professional sports leagues often have a “free agency” period, during which teams may sign players with expiring contracts.To promote parity, many leagues operate under a salary cap that limits the amount teams can spend on player’s salaries in a given year. Similarly, in fantasy sports leagues, salary cap drafts are a popular method for selecting players. In order to sign a free agent in either setting, teams must bid against one another to buy the player’s services while ensuring the sum of their player’s salaries is below the salary cap. This paper models the bidding process for a free agent as a constrained optimization problem that can be solved using linear programming. The objective is to determine the largest bid that a team should offer the player subject to the constraint that the value of signing the player must exceed the value of using the salary cap elsewhere. Iteratively solving this optimization problem for each available free agent provides teams with an effective framework for maximizing the talent on their rosters. The utility of this approach is demonstrated for team sport roster construction and fantasy sport drafts, using recent data sets from both settings.

Keywords: linear programming, optimization, roster management, salary cap

Procedia PDF Downloads 98
8298 Quantitative Structure-Activity Relationship Modeling of Detoxication Properties of Some 1,2-Dithiole-3-Thione Derivatives

Authors: Nadjib Melkemi, Salah Belaidi

Abstract:

Quantitative Structure-Activity Relationship (QSAR) studies have been performed on nineteen molecules of 1,2-dithiole-3-thione analogues. The compounds used are the potent inducers of enzymes involved in the maintenance of reduced glutathione pools as well as phase-2 enzymes important to electrophile detoxication. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and detoxication properties of the 1,2-dithiole-3-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: qS2, qC3, qC5, qS6, DM, Pol, log P, MV, SAG, HE and EHOMO for the specific activity of quinone reductase; qS1, qS2, qC3, qC4, qC5, qS6, DM, Pol, logP, MV, SAG, HE and EHOMO for the production of growth hormone. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.

Keywords: QSAR, quinone reductase activity, production of growth hormone, MLR

Procedia PDF Downloads 330
8297 On the Algorithmic Iterative Solutions of Conjugate Gradient, Gauss-Seidel and Jacobi Methods for Solving Systems of Linear Equations

Authors: Hussaini Doko Ibrahim, Hamilton Cyprian Chinwenyi, Henrietta Nkem Ude

Abstract:

In this paper, efforts were made to examine and compare the algorithmic iterative solutions of the conjugate gradient method as against other methods such as Gauss-Seidel and Jacobi approaches for solving systems of linear equations of the form Ax=b, where A is a real n×n symmetric and positive definite matrix. We performed algorithmic iterative steps and obtained analytical solutions of a typical 3×3 symmetric and positive definite matrix using the three methods described in this paper (Gauss-Seidel, Jacobi, and conjugate gradient methods), respectively. From the results obtained, we discovered that the conjugate gradient method converges faster to exact solutions in fewer iterative steps than the two other methods, which took many iterations, much time, and kept tending to the exact solutions.

Keywords: conjugate gradient, linear equations, symmetric and positive definite matrix, gauss-seidel, Jacobi, algorithm

Procedia PDF Downloads 134
8296 Proposal of a Model Supporting Decision-Making Based on Multi-Objective Optimization Analysis on Information Security Risk Treatment

Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

Abstract:

Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

Procedia PDF Downloads 444
8295 A Fundamental Study on the Anchor Performance of Non-Surface Treated Multi CFRP Tendons

Authors: Woo-tai Jung, Jong-sup Park, Jae-yoon Kang, Moon-seoung Keum

Abstract:

CFRP (Carbon Fiber Reinforced Polymer) is mainly used as reinforcing material for degraded structures owing to its advantages including its non-corrodibility, high strength, and lightweight properties. Recently, dedicated studies focused not only on its simple bonding but also on its tensioning. The tension necessary for prestressing requires the anchoring of multi-CFRP tendons with high capacity and the surface treatment of the CFRP tendons may also constitute an important issue according to the type of anchor. The wedge type, swage type or bonded type anchor can be used to anchor the CFRP tendon. The bonded type anchor presents the disadvantage to lengthen the length of the anchor due to the low bond strength of the CFRP tendon without surface treatment. This study intends to overcome this drawback through the application of a method enlarging the bond area at the end of the CFRP tendon. This method enlarges the bond area by splitting the end of the CFRP tendon along its length and can be applied when CFRP is produced by pultrusion. The application of this method shows that the mono-CFRP tendon and 3-multi CFRP tendon secured the anchor performance corresponding to the tensile performance of the CFRP tendon and that the 7-multi tendon secured anchor performance corresponding to 90% of the tensile strength due to the occurrence of buckling in the steel tube anchorage.

Keywords: carbon fiber reinforced polymer (CFRP), tendon, anchor, tensile property, bond strength

Procedia PDF Downloads 233
8294 Seismic Response Mitigation of Structures Using Base Isolation System Considering Uncertain Parameters

Authors: Rama Debbarma

Abstract:

The present study deals with the performance of Linear base isolation system to mitigate seismic response of structures characterized by random system parameters. This involves optimization of the tuning ratio and damping properties of the base isolation system considering uncertain system parameters. However, the efficiency of base isolator may reduce if it is not tuned to the vibrating mode it is designed to suppress due to unavoidable presence of system parameters uncertainty. With the aid of matrix perturbation theory and first order Taylor series expansion, the total probability concept is used to evaluate the unconditional response of the primary structures considering random system parameters. For this, the conditional second order information of the response quantities are obtained in random vibration framework using state space formulation. Subsequently, the maximum unconditional root mean square displacement of the primary structures is used as the objective function to obtain optimum damping parameters Numerical study is performed to elucidate the effect of parameters uncertainties on the optimization of parameters of linear base isolator and system performance.

Keywords: linear base isolator, earthquake, optimization, uncertain parameters

Procedia PDF Downloads 408
8293 Frequency Identification of Wiener-Hammerstein Systems

Authors: Brouri Adil, Giri Fouad

Abstract:

The problem of identifying Wiener-Hammerstein systems is addressed in the presence of two linear subsystems of structure totally unknown. Presently, the nonlinear element is allowed to be noninvertible. The system identification problem is dealt by developing a two-stage frequency identification method such a set of points of the nonlinearity are estimated first. Then, the frequency gains of the two linear subsystems are determined at a number of frequencies. The method involves Fourier series decomposition and only requires periodic excitation signals. All involved estimators are shown to be consistent.

Keywords: Wiener-Hammerstein systems, Fourier series expansions, frequency identification, automation science

Procedia PDF Downloads 517
8292 Steady-State Behavior of a Multi-Phase M/M/1 Queue in Random Evolution Subject to Catastrophe Failure

Authors: Reni M. Sagayaraj, Anand Gnana S. Selvam, Reynald R. Susainathan

Abstract:

In this paper, we consider stochastic queueing models for Steady-state behavior of a multi-phase M/M/1 queue in random evolution subject to catastrophe failure. The arrival flow of customers is described by a marked Markovian arrival process. The service times of different type customers have a phase-type distribution with different parameters. To facilitate the investigation of the system we use a generalized phase-type service time distribution. This model contains a repair state, when a catastrophe occurs the system is transferred to the failure state. The paper focuses on the steady-state equation, and observes that, the steady-state behavior of the underlying queueing model along with the average queue size is analyzed.

Keywords: M/G/1 queuing system, multi-phase, random evolution, steady-state equation, catastrophe failure

Procedia PDF Downloads 311
8291 Comparison of Parallel CUDA and OpenMP Implementations of Memetic Algorithms for Solving Optimization Problems

Authors: Jason Digalakis, John Cotronis

Abstract:

Memetic algorithms (MAs) are useful for solving optimization problems. It is quite difficult to search the search space of the optimization problem with large dimensions. There is a challenge to use all the cores of the system. In this study, a sequential implementation of the memetic algorithm is converted into a concurrent version, which is executed on the cores of both CPU and GPU. For this reason, CUDA and OpenMP libraries are operated on the parallel algorithm to make a concurrent execution on CPU and GPU, respectively. The aim of this study is to compare CPU and GPU implementation of the memetic algorithm. For this purpose, fourteen benchmark functions are selected as test problems. The obtained results indicate that our approach leads to speedups up to five thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have the potential to acceleration of MAs and allow them to solve much more complex tasks.

Keywords: memetic algorithm, CUDA, GPU-based memetic algorithm, open multi processing, multimodal functions, unimodal functions, non-linear optimization problems

Procedia PDF Downloads 78
8290 Investigating the Influence of the Ferro Alloys Consumption on the Slab Product Standard Cost with Different Grades Using Regression Analysis (A Case Study of Iran's Iron and Steel Industry)

Authors: Iman Fakhrian, Ali Salehi Manzari

Abstract:

Consistent Profitability is one of the most important priorities in manufacturing companies. One of the fundamental factors for increasing the companies profitability is cost management. Isfahan's mobarakeh steel company is one of the largest producers of the slab product grades in the middle east. Raw material cost constitutes about 70% of the company's expenditures. The costs of the ferro alloys have a remarkable contribution of the raw material costs. This research aims to determine the ferro alloys which have significant effect on the variability of the standard cost of the slab product grades. Used data in this study were collected from standard costing system of isfahan's mobarakeh steel company in 2022. The results of conducting the regression analysis model show that expense items: 03020, 03045, 03125, 03130 and 03150 have dominant role in variability of the standard cost of the slab product grades. In other words, the mentioned ferro alloys have noticeable and significant role in variability of the standard cost of the slab product grades.

Keywords: consistent profitability, ferro alloys, slab product grades, regression analysis

Procedia PDF Downloads 52
8289 Implication of Multi-Walled Carbon Nanotubes on Polymer/MXene Nanocomposites

Authors: Mathias Aakyiir, Qunhui Zheng, Sherif Araby, Jun Ma

Abstract:

MXene nanosheets stack in polymer matrices, while multi-walled carbon nanotubes (MWCNTs) entangle themselves when used to form composites. These challenges are addressed in this work by forming MXene/MWCNT hybrid nanofillers by electrostatic self-assembly and developing elastomer/MXene/MWCNTs nanocomposites using a latex compounding method. In a 3-phase nanocomposite, MWCNTs serve as bridges between MXene nanosheets, leading to nanocomposites with well-dispersed nanofillers. The high aspect ratio of MWCNTs and the interconnection role of MXene serve as a basis for forming nanocomposites of lower percolation threshold of electrical conductivity from the hybrid fillers compared with the 2-phase composites containing either MXene or MWCNTs only. This study focuses on discussing into detail the interfacial interaction of nanofillers and the elastomer matrix and the outstanding mechanical and functional properties of the resulting nanocomposites. The developed nanocomposites have potential applications in the automotive and aerospace industries.

Keywords: elastomers, multi-walled carbon nanotubes, MXenes, nanocomposites

Procedia PDF Downloads 147
8288 Create a Brand Value Assessment Model to Choosing a Cosmetic Brand in Tehran Combining DEMATEL Techniques and Multi-Stage ANFIS

Authors: Hamed Saremi, Suzan Taghavy, Seyed Mohammad Hanif Sanjari, Mostafa Kahali

Abstract:

One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study, the identified indicators of brand equity are based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: brand, cosmetic product, ANFIS, DEMATEL

Procedia PDF Downloads 403
8287 Production Plan and Technological Variants Optimization by Goal Programming Methods

Authors: Tunjo Perić, Franjo Bratić

Abstract:

In this paper the goal programming methodology for solving multiple objective problem of the technological variants and production plan optimization has been applied. The optimization criteria are determined and the multiple objective linear programming model for solving a problem of the technological variants and production plan optimization is formed and solved. Then the obtained results are analysed. The obtained results point out to the possibility of efficient application of the goal programming methodology in solving the problem of the technological variants and production plan optimization. The paper points out on the advantages of the application of the goal programming methodolohy compare to the Surrogat Worth Trade-off method in solving this problem.

Keywords: goal programming, multi objective programming, production plan, SWT method, technological variants

Procedia PDF Downloads 356
8286 Extended Literature Review on Sustainable Energy by Using Multi-Criteria Decision Making Techniques

Authors: Koray Altintas, Ozalp Vayvay

Abstract:

Increased global issues such as depletion of sources, environmental problems and social inequality triggered public awareness towards finding sustainable solutions in order to ensure the well-being of the current as well as future generations. Since energy plays a significant role in improved social and economic well-being and is imperative on both industrial and commercial wealth creation, it is a must to develop a standardized set of metrics which makes it possible to indicate the present condition relative to conditions in the past and to develop any perspective which is required to frame actions for the future. This is not an easy task by considering the complexity of the issue which requires integrating economic, environmental and social aspects of sustainable energy. Multi-criteria decision making (MCDM) can be considered as a form of integrated sustainability evaluation and a decision support approach that can be used to solve complex problems featuring; conflicting objectives, different forms of data and information, multi-interests and perspectives. On that matter, MCDM methods are useful for providing solutions to complex energy management problems. The aim of this study is to review MCDM approaches that can be used for examining sustainable energy management. This study presents an insight into MCDM techniques and methods that can be useful for engineers, researchers and policy makers working in the energy sector.

Keywords: sustainable energy, sustainability criteria, multi-criteria decision making, sustainability dimensions

Procedia PDF Downloads 306
8285 A Cheap Mesoporous Silica from Fly Ash as an Adsorbent for Sulfate in Water

Authors: Ximena Castillo, Jaime Pizarro

Abstract:

This research describes the development of a very cheap mesoporous silica material similar to hexagonal mesoporous silica (HMS) and using a silicate extract as precursor. This precursor is obtained from cheap fly ash by an easy calcination process at 850 °C and a green extraction with water. The obtained mesoporous fly ash material had a surface area of 282 m2 g-1 and a pore size of 5.7 nm. It was functionalized with ethylene diamino moieties via the well-known SAMMS method, followed by a DRIFT analysis that clearly showed the successful functionalization. An excellent adsorbent was obtained for the adsorption of sulfate anions by the solid’s modification with copper forming a copper-ethylenediamine complex. The adsorption of sulfates was studied in a batch system ( experimental conditions: pH=8.0; 5 min). The kinetics data were adjusted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model. The maximum sulfate adsorption capacity of this very cheap fly ash based adsorbent was 146.1 mg g-1, 3 times greater than the values reported in literature and commercial adsorbent materials.

Keywords: fly ash, mesoporous materials, SAMMS, sulfate

Procedia PDF Downloads 163
8284 Multi-Classification Deep Learning Model for Diagnosing Different Chest Diseases

Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

Abstract:

Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

Procedia PDF Downloads 74
8283 Active Linear Quadratic Gaussian Secondary Suspension Control of Flexible Bodied Railway Vehicle

Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

Abstract:

Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

Procedia PDF Downloads 243
8282 A Fluorescent Polymeric Boron Sensor

Authors: Soner Cubuk, Mirgul Kosif, M. Vezir Kahraman, Ece Kok Yetimoglu

Abstract:

Boron is an essential trace element for the completion of the life circle for organisms. Suitable methods for the determination of boron have been proposed, including acid - base titrimetric, inductively coupled plasma emission spectroscopy flame atomic absorption and spectrophotometric. However, the above methods have some disadvantages such as long analysis times, requirement of corrosive media such as concentrated sulphuric acid and multi-step sample preparation requirements and time-consuming procedures. In this study, a selective and reusable fluorescent sensor for boron based on glycosyloxyethyl methacrylate was prepared by photopolymerization. The response characteristics such as response time, pH, linear range, limit of detection were systematically investigated. The excitation/emission maxima of the membrane were at 378/423 nm, respectively. The approximate response time was measured as 50 sec. In addition, sensor had a very low limit of detection which was 0.3 ppb. The sensor was successfully used for the determination of boron in water samples with satisfactory results.

Keywords: boron, fluorescence, photopolymerization, polymeric sensor

Procedia PDF Downloads 267
8281 A Multi Agent Based Protection Scheme for Smart Distribution Network in Presence of Distributed Energy Resources

Authors: M. R. Ebrahimi, B. Mahdaviani

Abstract:

Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

Procedia PDF Downloads 592
8280 Multivalued Behavior for a Two-Level System Using Homotopy Analysis Method

Authors: Angelo I. Aquino, Luis Ma. T. Bo-ot

Abstract:

We use the Homotopy Analysis Method (HAM) to solve the system of equations modeling the two-level system and extract results which will pinpoint to turbulent behavior. We look at multi-valued solutions as indicative of turbulence or turbulent-like behavior. We take di erent speci c cases which result in multi-valued velocities. The solutions are in series form and application of HAM ensures convergence in some region.

Keywords: multivalued solutions, homotopy analysis method, two-level system, equation

Procedia PDF Downloads 581
8279 Is There Relationship between Cyberchondria and Emotional Intelligence among Omani University Students? A Descriptive Correlational Study

Authors: Mohammed Qutishat, Khaldoun Aldiabat, Khaled Bader, Mohammad Al Qadire

Abstract:

Cyberchondria refers to the irrational increase of distress about the condition of one's health as a consequence of the World Wide Web quest for medical details. The aim of this study was to examine the relationship between emotional intelligence and cyberchondria among Omani university students. A descriptive correlational design was used to collect data from eligible 370 participants using the Emotional Intelligence Questionnaire, and the short-form version of the Cyberchondria Severity Scale (CSS-12) between January and May 2020 at XX University-Oman. The participants’ age ranged between 18 and 37 years (M = 20.28). The majority of the participants were female, 59.7% (n = 221), single 99.5% (368), in their second academic year, 29.2% (n =108). The mean score of cyberchondria experiences was 32.51, and the mean score of emotional intelligence was 34.91. Linear regression indicated a strong association between cyberchondria and emotional intelligence [F (34.639) = 5.885, P=.000], with a .086 R². In conclusion, the exchange of expertise and peer networking for health-related details utilizing the Internet can benefit students with and without having health problems. Further research and methods should be developed to help students track the online medical tools effectively for the right purposes.

Keywords: emotional intelligence, cyberchondria, smartphone addiction, social media

Procedia PDF Downloads 230
8278 Optimization of Solar Rankine Cycle by Exergy Analysis and Genetic Algorithm

Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon

Abstract:

Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.

Keywords: exergy analysis, genetic algorithm, rankine cycle, single and multi-objective function

Procedia PDF Downloads 134
8277 Long-Term Indoor Air Monitoring for Students with Emphasis on Particulate Matter (PM2.5) Exposure

Authors: Seyedtaghi Mirmohammadi, Jamshid Yazdani, Syavash Etemadi Nejad

Abstract:

One of the main indoor air parameters in classrooms is dust pollution and it depends on the particle size and exposure duration. However, there is a lake of data about the exposure level to PM2.5 concentrations in rural area classrooms. The objective of the current study was exposure assessment for PM2.5 for students in the classrooms. One year monitoring was carried out for fifteen schools by time-series sampling to evaluate the indoor air PM2.5 in the rural district of Sari city, Iran. A hygrometer and thermometer were used to measure some psychrometric parameters (temperature, relative humidity, and wind speed) and Real-Time Dust Monitor, (MicroDust Pro, Casella, UK) was used to monitor particulate matters (PM2.5) concentration. The results show the mean indoor PM2.5 concentration in the studied classrooms was 135µg/m3. The regression model indicated that a positive correlation between indoor PM2.5 concentration and relative humidity, also with distance from city center and classroom size. Meanwhile, the regression model revealed that the indoor PM2.5 concentration, the relative humidity, and dry bulb temperature was significant at 0.05, 0.035, and 0.05 levels, respectively. A statistical predictive model was obtained from multiple regressions modeling for indoor PM2.5 concentration and indoor psychrometric parameters conditions.

Keywords: classrooms, concentration, humidity, particulate matters, regression

Procedia PDF Downloads 318
8276 An Application of Sinc Function to Approximate Quadrature Integrals in Generalized Linear Mixed Models

Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

Abstract:

This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

Procedia PDF Downloads 381
8275 Iterative Linear Quadratic Regulator (iLQR) vs LQR Controllers for Quadrotor Path Tracking

Authors: Wesam Jasim, Dongbing Gu

Abstract:

This paper presents an iterative linear quadratic regulator optimal control technique to solve the problem of quadrotors path tracking. The dynamic motion equations are represented based on unit quaternion representation and include some modelled aerodynamical effects as a nonlinear part. Simulation results prove the ability and effectiveness of iLQR to stabilize the quadrotor and successfully track different paths. It also shows that iLQR controller outperforms LQR controller in terms of fast convergence and tracking errors.

Keywords: iLQR controller, optimal control, path tracking, quadrotor UAVs

Procedia PDF Downloads 424
8274 Optimal Control of DC Motor Using Linear Quadratic Regulator

Authors: Meetty Tomy, Arxhana G Thosar

Abstract:

This paper provides the implementation of optimal control for an armature-controlled DC motor. The selection of error weighted Matrix and control weighted matrix in order to implement optimal control theory for improving the dynamic behavior of DC motor is presented. The closed loop performance of Armature controlled DC motor with derived linear optimal controller is then evaluated for the transient operating condition (starting). The result obtained from MATLAB is compared with that of PID controller and simple closed loop response of the motor.

Keywords: optimal control, DC motor, performance index, MATLAB

Procedia PDF Downloads 393
8273 The Relationship between Amplitude and Stability of Circadian Rhythm with Sleep Quality and Sleepiness: A Population Study, Kerman 2018

Authors: Akram Sadat Jafari Roodbandi, Farzaneh Akbari, Vafa Feyzi, Zahra Zare, Zohreh Foroozanfar

Abstract:

Introduction: Circadian rhythm or sleep-awake cycle in 24 hours is one of the important factors affecting the physiological and psychological characteristics in humans that contribute to biochemical, physiological and behavioral processes and helps people to set up brain and body for sleep or active awakening during certain hours. The purpose of this study was to investigate the relationship between the characteristics of circadian rhythms on the sleep quality and sleepiness according to their demographic characteristics such as age. Methods: This cross-sectional descriptive-analytic study was carried out among the general population of Kerman, aged 15-84 years. After dividing the age groups into 10-year demographic characteristics questionnaire, the type of circadian questionnaire, Pittsburgh sleep quality questionnaire and Euporth sleepiness questionnaire were completed in equal numbers between men and women of that age group. Using cluster sampling with effect design equal 2, 1300 questionnaires were distributed during the various hours of 24 hours in public places in Kerman city. Data analysis was done using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: In this study, 1147 subjects were included in the study, 584 (50.9%) were male and the rest were women. The mean age was 39.50 ± 15.38. 133 (11.60%) subjects from the study participants had sleepiness and 308 (26.90%) subjects had undesirable sleep quality. Using linear regression test, sleep quality was the significant correlation with sex, hours needed for sleep at 24 hours, chronic illness, sleepiness, and circadian rhythm amplitude. Sleepiness was the meaningful relationship with marital status, sleep-wake schedule of other family members and the stability of circadian rhythm. Both women and men, with age, decrease the quality of sleep and increase the rate of sleepiness. Conclusion: Age, sex, and type of circadian people, the need for sleep at 24 hours, marital status, sleep-wake schedule of other family members are significant factors related to the sleep quality and sleepiness and their adaptation to night shift work.

Keywords: circadian type, sleep quality, sleepiness, age, shift work

Procedia PDF Downloads 137