Search results for: double nonlinear predictive controller
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4128

Search results for: double nonlinear predictive controller

2418 Intelligent Control Design of Car Following Behavior Using Fuzzy Logic

Authors: Abdelkader Merah, Kada Hartani

Abstract:

A reference model based control approach for improving behavior following car is proposed in this paper. The reference model is nonlinear and provides dynamic solutions consistent with safety constraints and comfort specifications. a robust fuzzy logic based control strategy is further proposed in this paper. A set of simulation results showing the suitability of the proposed technique for various demanding cenarios is also included in this paper.

Keywords: reference model, longitudinal control, fuzzy logic, design of car

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2417 Development of a Novel Clinical Screening Tool, Using the BSGE Pain Questionnaire, Clinical Examination and Ultrasound to Predict the Severity of Endometriosis Prior to Laparoscopic Surgery

Authors: Marlin Mubarak

Abstract:

Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

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2416 Contribution to the Decision-Making Process for Selecting the Suitable Maintenance Policy

Authors: Nasser Y. Mahamoud, Pierre Dehombreux, Hassan E. Robleh

Abstract:

Industrial companies may be confronted with questions about their choice of maintenance policy. This choice must be guided by several numbers of decision criteria or objectives related to their production or service activities but also to their level of development and their investment prospects. A decision-support methodology to choose a maintenance policy (corrective, systematic or conditional preventive, predictive, opportunistic or not) is proposed to facilitate this choice using the main categories of the most important decision criteria. The different steps of this methodology are illustrated using theoretical case: identification of the different maintenance alternatives, determining the structure of the most important categories of the decision criteria, assessing the different maintenance policies on to the criteria by using an ordinal preference relation, and finally ranking the different maintenance policies.

Keywords: maintenance policy, decision criteria, decision-making process, AHP

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2415 An Efficient Automated Radiation Measuring System for Plasma Monopole Antenna

Authors: Gurkirandeep Kaur, Rana Pratap Yadav

Abstract:

This experimental study is aimed to examine the radiation characteristics of different plasma structures of a surface wave-driven plasma antenna by an automated measuring system. In this study, a 30 cm long plasma column of argon gas with a diameter of 3 cm is excited by surface wave discharge mechanism operating at 13.56 MHz with RF power level up to 100 Watts and gas pressure between 0.01 to 0.05 mb. The study reveals that a single structured plasma monopole can be modified into an array of plasma antenna elements by forming multiple striations or plasma blobs inside the discharge tube by altering the values of plasma properties such as working pressure, operating frequency, input RF power, discharge tube dimensions, i.e., length, radius, and thickness. It is also reported that plasma length, electron density, and conductivity are functions of operating plasma parameters and controlled by changing working pressure and input power. To investigate the antenna radiation efficiency for the far-field region, an automation-based radiation measuring system has been fabricated and presented in detail. This developed automated system involves a combined setup of controller, dc servo motors, vector network analyzer, and computing device to evaluate the radiation intensity, directivity, gain and efficiency of plasma antenna. In this system, the controller is connected to multiple motors for moving aluminum shafts in both elevation and azimuthal plane whereas radiation from plasma monopole antenna is measured by a Vector Network Analyser (VNA) which is further wired up with the computing device to display radiations in polar plot forms. Here, the radiation characteristics of both continuous and array plasma monopole antenna have been studied for various working plasma parameters. The experimental results clearly indicate that the plasma antenna is as efficient as a metallic antenna. The radiation from plasma monopole antenna is significantly influenced by plasma properties which provides a wider range in radiation pattern where desired radiation parameters like beam-width, the direction of radiation, radiation intensity, antenna efficiency, etc. can be achieved in a single monopole. Due to its wide range of selectivity in radiation pattern; this can meet the demands of wider bandwidth to get high data speed in communication systems. Moreover, this developed system provides an efficient and cost-effective solution for measuring the radiation pattern in far-field zone for any kind of antenna system.

Keywords: antenna radiation characteristics, dynamically reconfigurable, plasma antenna, plasma column, plasma striations, surface wave

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2414 Methodology for Obtaining Static Alignment Model

Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

Abstract:

In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: information theory, prediction model, prosthetic alignment, transtibial prosthesis

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2413 The Foucaultian Relationship between Power and Knowledge: Genealogy as a Method for Epistemic Resistance

Authors: Jana Soler Libran

Abstract:

The primary aim of this paper is to analyze the relationship between power and knowledge suggested in Michel Foucault's theory. Taking into consideration the role of power in knowledge production, the goal is to evaluate to what extent genealogy can be presented as a practical method for epistemic resistance. To do so, the methodology used consists of a revision of Foucault’s literature concerning the topic discussed. In this sense, conceptual analysis is applied in order to understand the effect of the double dimension of power on knowledge production. In its negative dimension, power is conceived as an organ of repression, vetoing certain instances of knowledge considered deceitful. In opposition, in its positive dimension, power works as an organ of the production of truth by means of institutionalized discourses. This double declination of power leads to the first main findings of the present analysis: no truth or knowledge can lie outside power’s action, and power is constituted through accepted forms of knowledge. To second these statements, Foucaultian discourse formations are evaluated, presenting external exclusion procedures as paradigmatic practices to demonstrate how power creates and shapes the validity of certain epistemes. Thus, taking into consideration power’s mechanisms to produce and reproduce institutionalized truths, this paper accounts for the Foucaultian praxis of genealogy as a method to reveal power’s intention, instruments, and effects in the production of knowledge. In this sense, it is suggested to consider genealogy as a practice which, firstly, reveals what instances of knowledge are subjugated to power and, secondly, promotes aforementioned peripherical discourses as a form of epistemic resistance. In order to counterbalance these main theses, objections to Foucault’s work from Nancy Fraser, Linda Nicholson, Charles Taylor, Richard Rorty, Alvin Goldman, or Karen Barad are discussed. In essence, the understanding of the Foucaultian relationship between power and knowledge is essential to analyze how contemporary discourses are produced by both traditional institutions and new forms of institutionalized power, such as mass media or social networks. Therefore, Michel Foucault's practice of genealogy is relevant, not only for its philosophical contribution as a method to uncover the effects of power in knowledge production but also because it constitutes a valuable theoretical framework for political theory and sociological studies concerning the formation of societies and individuals in the contemporary world.

Keywords: epistemic resistance, Foucault’s genealogy, knowledge, power, truth

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2412 Predicting Football Player Performance: Integrating Data Visualization and Machine Learning

Authors: Saahith M. S., Sivakami R.

Abstract:

In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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2411 Reductive Control in the Management of Redundant Actuation

Authors: Mkhinini Maher, Knani Jilani

Abstract:

We present in this work the performances of a mobile omnidirectional robot through evaluating its management of the redundancy of actuation. Thus we come to the predictive control implemented. The distribution of the wringer on the robot actions, through the inverse pseudo of Moore-Penrose, corresponds to a -geometric- distribution of efforts. We will show that the load on vehicle wheels would not be equi-distributed in terms of wheels configuration and of robot movement. Thus, the threshold of sliding is not the same for the three wheels of the vehicle. We suggest exploiting the redundancy of actuation to reduce the risk of wheels sliding and to ameliorate, thereby, its accuracy of displacement. This kind of approach was the subject of study for the legged robots.

Keywords: mobile robot, actuation, redundancy, omnidirectional, inverse pseudo moore-penrose, reductive control

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2410 Artificial Neural Networks in Environmental Psychology: Application in Architectural Projects

Authors: Diego De Almeida Pereira, Diana Borchenko

Abstract:

Artificial neural networks are used for many applications as they are able to learn complex nonlinear relationships between input and output data. As the number of neurons and layers in a neural network increases, it is possible to represent more complex behaviors. The present study proposes that artificial neural networks are a valuable tool for architecture and engineering professionals concerned with understanding how buildings influence human and social well-being based on theories of environmental psychology.

Keywords: environmental psychology, architecture, neural networks, human and social well-being

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2409 Developing and Shake Table Testing of Semi-Active Hydraulic Damper as Active Interaction Control Device

Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

Abstract:

Semi-active control system for structure under excitation of earthquake provides with the characteristics of being adaptable and requiring low energy. DSHD (Displacement Semi-Active Hydraulic Damper) was developed by our research team. Shake table test results of this DSHD installed in full scale test structure demonstrated that this device brought its energy-dissipating performance into full play for test structure under excitation of earthquake. The objective of this research is to develop a new AIC (Active Interaction Control Device) and apply shake table test to perform its dissipation of energy capability. This new proposed AIC is converting an improved DSHD (Displacement Semi-Active Hydraulic Damper) to AIC with the addition of an accumulator. The main concept of this energy-dissipating AIC is to apply the interaction function of affiliated structure (sub-structure) and protected structure (main structure) to transfer the input seismic force into sub-structure to reduce the structural deformation of main structure. This concept is tested using full-scale multi-degree of freedoms test structure, installed with this proposed AIC subjected to external forces of various magnitudes, for examining the shock absorption influence of predictive control, stiffness of sub-structure, synchronous control, non-synchronous control and insufficient control position. The test results confirm: (1) this developed device is capable of diminishing the structural displacement and acceleration response effectively; (2) the shock absorption of low precision of semi-active control method did twice as much seismic proof efficacy as that of passive control method; (3) active control method may not exert a negative influence of amplifying acceleration response of structure; (4) this AIC comes into being time-delay problem. It is the same problem of ordinary active control method. The proposed predictive control method can overcome this defect; (5) condition switch is an important characteristics of control type. The test results show that synchronism control is very easy to control and avoid stirring high frequency response. This laboratory results confirm that the device developed in this research is capable of applying the mutual interaction between the subordinate structure and the main structure to be protected is capable of transforming the quake energy applied to the main structure to the subordinate structure so that the objective of minimizing the deformation of main structural can be achieved.

Keywords: DSHD (Displacement Semi-Active Hydraulic Damper), AIC (Active Interaction Control Device), shake table test, full scale structure test, sub-structure, main-structure

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2408 Tracking Trajectory of a Cable-Driven Robot for Lower Limb Rehabilitation

Authors: Hachmia Faqihi, Maarouf Saad, Khalid Benjelloun, Mohammed Benbrahim, M. Nabil Kabbaj

Abstract:

This paper investigates and presents a cable-driven robot to lower limb rehabilitation use in sagittal plane. The presented rehabilitation robot is used for a trajectory tracking in joint space. The paper covers kinematic and dynamic analysis, which reveals the tensionability of the used cables as being the actuating source to provide a rehabilitation exercises of the human leg. The desired trajectory is generated to be used in the control system design in joint space. The obtained simulation results is showed to be efficient in this kind of application.

Keywords: cable-driven multi-body system, computed-torque controller, lower limb rehabilitation, tracking trajectory

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2407 A Safety-Door for Earthquake Disaster Prevention - Part II

Authors: Daniel Y. Abebe, Jaehyouk Choi

Abstract:

The safety of door has not given much attention. The main problem of doors during and after earthquake is that they are unable to be opened because deviation from its original position by the lateral load. The aim of this research is to develop and evaluate a safety door that keeps the door frame in its original position or keeps its edge angles perpendicular during and post-earthquake. Nonlinear finite element analysis was conducted in order to evaluate the structural performance and behavior of the proposed door under both monotonic and cyclic loading.

Keywords: safety-door, earthquake disaster, low yield point steel, passive energy dissipating device, FE analysis

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2406 Effects of Fatty Acid Salts and Spices on Dermatophagoides farinae

Authors: Yumeho Obata, Mariko Era, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

Abstract:

Dermatophagoides farinae is major mite allergens in indoors. D. farinae is often swarm over powder products (e.g. wheat flour), because it feeds on starch or protein that are included in them. Eating powder products which are mixed D.farinae causes various allergic symptoms. Therefore, the creation of food additive agents with high safety and control of mite effect is required. Fatty acid salts and spices are known that have pesticidal activities. This study describes the effects of fatty acid salts and spices against Dermatophagoides farinae. Materials and Methods: Potassium salts of 9 fatty acids (C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C18:1, C18:2, C18:3) were prepared by mixing the fatty acid with the appropriate amount of KOH solution to a concentration of 175 mM and pH 10.5. C12Cu and C12Zn were selected as other fatty acid salts. Cayenne pepper, habanero, Japanese pepper, mustard, jalapeno pepper, curry aroma and cinnamon were selected as spices. D. farina, have been cultured in laboratory. To rear the mites, double-soled dishes containing of sterilized food were put on the big plastic container (30.0 × 20.0 × 20.0cm) which had 100% ammonium nitrate solution in the bottom. Plastic container was placed on incubator at 25 °C and 64 % relative humidity (RH) under dark condition. Sterilized food composed of dried bonito flakes and dried yeast (Ebios), 1:1 by weight. The antiproliferative method, sample and medium culture were mixed in double-soled dish and kept at 25 °C and 64 % RH. Decrease rates were determined 1 week and 4 week after treatment under microscope. D. farina was considered to be dead if appendages did not move when prodded with a pin. Results and Conclusions: The results show that the fatty acids potassium showed no antiproliferative effects against D. farinae. On the other hand, Japanese pepper, mustard, curry aroma and cinnamon were effective to decrease propagative rate (over 80 %) after treatment for 1 week against D. farina. Japanese pepper, curry aroma and cinnamon were effective to decrease propagative rate (approximately 100 %) after treatment for 4 weeks against D. farina. Especially, Japanese pepper and cinnamon showed the fasted and the most consecutive antiproliferative effects. These results indicate that Japanese pepper and cinnamon have high antiproliferative effects against D. farina and suggest spices will be used as a food additive agent.

Keywords: fatty acid salts, spices, antiproliferative effects, dermatophagoides farinae

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2405 Numerical Solutions of Generalized Burger-Fisher Equation by Modified Variational Iteration Method

Authors: M. O. Olayiwola

Abstract:

Numerical solutions of the generalized Burger-Fisher are obtained using a Modified Variational Iteration Method (MVIM) with minimal computational efforts. The computed results with this technique have been compared with other results. The present method is seen to be a very reliable alternative method to some existing techniques for such nonlinear problems.

Keywords: burger-fisher, modified variational iteration method, lagrange multiplier, Taylor’s series, partial differential equation

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2404 Antihypertensive Effect of Formulated Apium graveolens: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial

Authors: Maryam Shayani Rad, Seyed Ahmad Mohajeri, Mohsen Mouhebati, Seyed Danial Mousavi

Abstract:

High blood pressure is one of the most important and serious health-threatening because of no symptoms in most people, which can lead to sudden heart attack, heart failure, and stroke. Nowadays, herbal medicine is one of the best and safest strategies for treatment that have no adverse effects. Apium graveolens (celery) can be used as an alternative treatment for many health conditions such as hypertension. Natural compounds reduce blood pressure via different mechanisms in which Apium graveolens extract provides potent calcium channel blocking properties. A randomized, double-blind, placebo-controlled, cross-over clinical trial was done to evaluate the efficacy of formulated Apium graveolens extract with a maximum yield of 3-n-butylphthalide to reduce systolic and diastolic blood pressure in patients with hypertension. 54 hypertensive patients in the range of 20-68 years old were randomly assigned to the treatment group (26 cases) and the placebo control group (26 cases) and were crossed over after washout duration. The treatment group received at least 2 grams of formulated powder in hard capsules orally, before each meal, 2 times daily. The control group received 2 grams of placebo in hard capsules orally, exactly as the same as shape, time, and doses of treatment group. Treatment was administrated in 12 weeks with 4 weeks washout period at the middle of the study, meaning 4 weeks drug consumption for the treatment group, 4 weeks washout and 4 weeks placebo consumption, and vice versa for the placebo control group. The clinical assessment was done 4 times, including at the beginning and ending of the drug and placebo consumption period by 24-hour ambulatory blood pressure monitoring (ABPM) holter, which measured blood pressure every 15 minutes continuously. There was a statistically significant decrease in both systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the end of drug duration compared to baseline. The changes after 4 weeks on average was about 12.34 mm Hg for the SBP (P < 0.005) and 7.83 mm Hg for the DBP (P < 0.005). The results from this clinical trial study showed this Apium graveolens extract formulation in the mentioned dosage had a significant effect on blood pressure-lowering for hypertensive patients.

Keywords: Apium graveolens extract, clinical trial, cross-over, hypertension

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2403 Numerical Model of Low Cost Rubber Isolators for Masonry Housing in High Seismic Regions

Authors: Ahmad B. Habieb, Gabriele Milani, Tavio Tavio, Federico Milani

Abstract:

Housings in developing countries have often inadequate seismic protection, particularly for masonry. People choose this type of structure since the cost and application are relatively cheap. Seismic protection of masonry remains an interesting issue among researchers. In this study, we develop a low-cost seismic isolation system for masonry using fiber reinforced elastomeric isolators. The elastomer proposed consists of few layers of rubber pads and fiber lamina, making it lower in cost comparing to the conventional isolators. We present a finite element (FE) analysis to predict the behavior of the low cost rubber isolators undergoing moderate deformations. The FE model of the elastomer involves a hyperelastic material property for the rubber pad. We adopt a Yeoh hyperelasticity model and estimate its coefficients through the available experimental data. Having the shear behavior of the elastomers, we apply that isolation system onto small masonry housing. To attach the isolators on the building, we model the shear behavior of the isolation system by means of a damped nonlinear spring model. By this attempt, the FE analysis becomes computationally inexpensive. Several ground motion data are applied to observe its sensitivity. Roof acceleration and tensile damage of walls become the parameters to evaluate the performance of the isolators. In this study, a concrete damage plasticity model is used to model masonry in the nonlinear range. This tool is available in the standard package of Abaqus FE software. Finally, the results show that the low-cost isolators proposed are capable of reducing roof acceleration and damage level of masonry housing. Through this study, we are also capable of monitoring the shear deformation of isolators during seismic motion. It is useful to determine whether the isolator is applicable. According to the results, the deformations of isolators on the benchmark one story building are relatively small.

Keywords: masonry, low cost elastomeric isolator, finite element analysis, hyperelasticity, damped non-linear spring, concrete damage plasticity

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2402 On Fault Diagnosis of Asynchronous Sequential Machines with Parallel Composition

Authors: Jung-Min Yang

Abstract:

Fault diagnosis of composite asynchronous sequential machines with parallel composition is addressed in this paper. An adversarial input can infiltrate one of two submachines comprising the composite asynchronous machine, causing an unauthorized state transition. The objective is to characterize the condition under which the controller can diagnose any fault occurrence. Two control configurations, state feedback and output feedback, are considered in this paper. In the case of output feedback, the exact estimation of the state is impossible since the current state is inaccessible and the output feedback is given as the form of burst. A simple example is provided to demonstrate the proposed methodology.

Keywords: asynchronous sequential machines, parallel composition, fault diagnosis, corrective control

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2401 Injury Prediction for Soccer Players Using Machine Learning

Authors: Amiel Satvedi, Richard Pyne

Abstract:

Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

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2400 Coefficients of Some Double Trigonometric Cosine and Sine Series

Authors: Jatinderdeep Kaur

Abstract:

In this paper, the results of Kano from one-dimensional cosine and sine series are extended to two-dimensional cosine and sine series. To extend these results, some classes of coefficient sequences such as the class of semi convexity and class R are extended from one dimension to two dimensions. Under these extended classes, I have checked the function f(x,y) is two dimensional Fourier Cosine and Sine series or equivalently it represents an integrable function. Further, some results are obtained which are the generalization of Moricz's results.

Keywords: conjugate dirichlet kernel, conjugate fejer kernel, fourier series, semi-convexity

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2399 Multi-Period Portfolio Optimization Using Predictive Machine Learning Models

Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

Abstract:

This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

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2398 Comparison of Power Generation Status of Photovoltaic Systems under Different Weather Conditions

Authors: Zhaojun Wang, Zongdi Sun, Qinqin Cui, Xingwan Ren

Abstract:

Based on multivariate statistical analysis theory, this paper uses the principal component analysis method, Mahalanobis distance analysis method and fitting method to establish the photovoltaic health model to evaluate the health of photovoltaic panels. First of all, according to weather conditions, the photovoltaic panel variable data are classified into five categories: sunny, cloudy, rainy, foggy, overcast. The health of photovoltaic panels in these five types of weather is studied. Secondly, a scatterplot of the relationship between the amount of electricity produced by each kind of weather and other variables was plotted. It was found that the amount of electricity generated by photovoltaic panels has a significant nonlinear relationship with time. The fitting method was used to fit the relationship between the amount of weather generated and the time, and the nonlinear equation was obtained. Then, using the principal component analysis method to analyze the independent variables under five kinds of weather conditions, according to the Kaiser-Meyer-Olkin test, it was found that three types of weather such as overcast, foggy, and sunny meet the conditions for factor analysis, while cloudy and rainy weather do not satisfy the conditions for factor analysis. Therefore, through the principal component analysis method, the main components of overcast weather are temperature, AQI, and pm2.5. The main component of foggy weather is temperature, and the main components of sunny weather are temperature, AQI, and pm2.5. Cloudy and rainy weather require analysis of all of their variables, namely temperature, AQI, pm2.5, solar radiation intensity and time. Finally, taking the variable values in sunny weather as observed values, taking the main components of cloudy, foggy, overcast and rainy weather as sample data, the Mahalanobis distances between observed value and these sample values are obtained. A comparative analysis was carried out to compare the degree of deviation of the Mahalanobis distance to determine the health of the photovoltaic panels under different weather conditions. It was found that the weather conditions in which the Mahalanobis distance fluctuations ranged from small to large were: foggy, cloudy, overcast and rainy.

Keywords: fitting, principal component analysis, Mahalanobis distance, SPSS, MATLAB

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2397 Nonlinear Power Measurement Algorithm of the Input Mix Components of the Noise Signal and Pulse Interference

Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

Abstract:

A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference to signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: noise signal, pulse interference, signal power, spectrum width, detection

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2396 Semilocal Convergence of a Three Step Fifth Order Iterative Method under Hölder Continuity Condition in Banach Spaces

Authors: Ramandeep Behl, Prashanth Maroju, S. S. Motsa

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In this paper, we study the semilocal convergence of a fifth order iterative method using recurrence relation under the assumption that first order Fréchet derivative satisfies the Hölder condition. Also, we calculate the R-order of convergence and provide some a priori error bounds. Based on this, we give existence and uniqueness region of the solution for a nonlinear Hammerstein integral equation of the second kind.

Keywords: Holder continuity condition, Frechet derivative, fifth order convergence, recurrence relations

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2395 Hidden Oscillations in the Mathematical Model of the Optical Binary Phase Shift Keying (BPSK) Costas Loop

Authors: N. V. Kuznetsov, O. A. Kuznetsova, G. A. Leonov, M. V. Yuldashev, R. V. Yuldashev

Abstract:

Nonlinear analysis of the phase locked loop (PLL)-based circuits is a challenging task. Thus, the simulation is widely used for their study. In this work, we consider a mathematical model of the optical Costas loop and demonstrate the limitations of simulation approach related to the existence of so-called hidden oscillations in the phase space of the model.

Keywords: optical Costas loop, mathematical model, simulation, hidden oscillation

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2394 Speed Power Control of Double Field Induction Generator

Authors: Ali Mausmi, Ahmed Abbou, Rachid El Akhrif

Abstract:

This research paper aims to reduce the chattering phenomenon due to control by sliding mode control applied on a wind energy conversion system based on the doubly fed induction generator (DFIG). Our goal is to offset the effect of parametric uncertainties and come as close as possible to the dynamic response solicited by the control law in the ideal case and therefore force the active and reactive power generated by the DFIG to accurately follow the reference values which are provided to it. The simulation results using Matlab / Simulink demonstrate the efficiency and performance of the proposed technique while maintaining the simplicity of control by first order sliding mode.

Keywords: control of speed, correction of the equivalent command, induction generator, sliding mode

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2393 Optimization of Transmission Loss on a Series-Coupled Muffler by Taguchi Method

Authors: Jing-Fung Lin, Jer-Jia Sheu

Abstract:

In this study, an approach has been developed for the noise reduction of a muffler. The transmission loss (TL) in the muffler is maximized by the use of a double-chamber muffler, and a baffle with a hole is inserted between chambers. Taguchi method is used to optimize the design for the acoustical performance of the muffler. The TL performance is evaluated by COMSOL software. The excellent parameter combination for the maximum TL is attained as high as 35.30 dB in a wide frequency range from 10 Hz to 1400 Hz. The influence sequence of four parameters on TL is determined by the range analysis. The effects of length and expansion ratio of the first chamber on TL performance for the excellent program were discussed. Comparisons of the TL results from different designs are made.

Keywords: acoustics, baffle, chamber, muffler, Taguchi method, transmission loss

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2392 Laser Beam Bending via Lenses

Authors: Remzi Yildirim, Fatih. V. Çelebi, H. Haldun Göktaş, A. Behzat Şahin

Abstract:

This study is about a single component cylindrical structured lens with gradient curve which we used for bending laser beams. It operates under atmospheric conditions and bends the laser beam independent of temperature, pressure, polarity, polarization, magnetic field, electric field, radioactivity, and gravity. A single piece cylindrical lens that can bend laser beams is invented. Lenses are made of transparent, tinted or colored glasses and used for undermining or absorbing the energy of the laser beams.

Keywords: laser, bending, lens, light, nonlinear optics

Procedia PDF Downloads 489
2391 Laser Light Bending via Lenses

Authors: Remzi Yildirim, Fatih V. Çelebi, H. Haldun Göktaş, A. Behzat Şahin

Abstract:

This study is about a single component cylindrical structured lens with gradient curve which we used for bending laser beams. It operates under atmospheric conditions and bends the laser beam independent of temperature, pressure, polarity, polarization, magnetic field, electric field, radioactivity, and gravity. A single piece cylindrical lens that can bend laser beams is invented. Lenses are made of transparent, tinted or colored glasses and used for undermining or absorbing the energy of the laser beams.

Keywords: laser, bending, lens, light, nonlinear optics

Procedia PDF Downloads 704
2390 Comparison of the Effectiveness of Tree Algorithms in Classification of Spongy Tissue Texture

Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

Abstract:

Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

Procedia PDF Downloads 182
2389 Fabrication and Analysis of Vertical Double-Diffused Metal Oxide Semiconductor (VDMOS)

Authors: Deepika Sharma, Bal Krishan

Abstract:

In this paper, the structure of N-channel VDMOS was designed and analyzed using Silvaco TCAD tools by varying N+ source doping concentration, P-Body doping concentration, gate oxide thickness and the diffuse time. VDMOS is considered to be ideal power switches due to its high input impedance and fast switching speed. The performance of the device was analyzed from the Ids vs Vgs curve. The electrical characteristics such as threshold voltage, gate oxide thickness and breakdown voltage for the proposed device structures were extarcted. Effect of epitaxial layer on various parameters is also observed.

Keywords: on-resistance, threshold voltage, epitaxial layer, breakdown voltage

Procedia PDF Downloads 329