Search results for: real time control

Authors: Mouna Essaadi, Mohamed Khafallah, Abdallah Saad, Hamid Chaikhy

Abstract:

This paper presents a comparative analysis between conventional direct torque control (C_DTC), Modified direct torque control (M_DTC) and twelve sectors direct torque control (12_DTC).Those different strategies are compared by simulation in term of torque, flux and stator current performances. Finally, a summary of the comparative analysis is presented.

Keywords: C_DTC, M_DTC, 12_DTC, torque dynamic, stator current, flux, performances

Procedia PDF Downloads 619

Authors: Anne Schattel, Mitja Echim, Christof Büskens

Abstract:

Trajectory planning for deep space missions has become a recent topic of great interest. Flying to space objects like asteroids provides two main challenges. One is to find rare earth elements, the other to gain scientific knowledge of the origin of the world. Due to the enormous spatial distances such explorer missions have to be performed unmanned and autonomously. The mathematical field of optimization and optimal control can be used to realize autonomous missions while protecting recourses and making them safer. The resulting algorithms may be applied to other, earth-bound applications like e.g. deep sea navigation and autonomous driving as well. The project KaNaRiA ('Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All') investigates the possibilities of cognitive autonomous navigation on the example of an asteroid mining mission, including the cruise phase and approach as well as the asteroid rendezvous, landing and surface exploration. To verify and test all methods an interactive, real-time capable simulation using virtual reality is developed under KaNaRiA. This paper focuses on the specific challenge of the guidance during the cruise phase of the spacecraft, i.e. trajectory optimization and optimal control, including first solutions and results. In principle there exist two ways to solve optimal control problems (OCPs), the so called indirect and direct methods. The indirect methods are being studied since several decades and their usage needs advanced skills regarding optimal control theory. The main idea of direct approaches, also known as transcription techniques, is to transform the infinite-dimensional OCP into a finite-dimensional non-linear optimization problem (NLP) via discretization of states and controls. These direct methods are applied in this paper. The resulting high dimensional NLP with constraints can be solved efficiently by special NLP methods, e.g. sequential quadratic programming (SQP) or interior point methods (IP). The movement of the spacecraft due to gravitational influences of the sun and other planets, as well as the thrust commands, is described through ordinary differential equations (ODEs). The competitive mission aims like short flight times and low energy consumption are considered by using a multi-criteria objective function. The resulting non-linear high-dimensional optimization problems are solved by using the software package WORHP ('We Optimize Really Huge Problems'), a software routine combining SQP at an outer level and IP to solve underlying quadratic subproblems. An application-adapted model of impulsive thrusting, as well as a model of an electrically powered spacecraft propulsion system, is introduced. Different priorities and possibilities of a space mission regarding energy cost and flight time duration are investigated by choosing different weighting factors for the multi-criteria objective function. Varying mission trajectories are analyzed and compared, both aiming at different destination asteroids and using different propulsion systems. For the transcription, the robust method of full discretization is used. The results strengthen the need for trajectory optimization as a foundation for autonomous decision making during deep space missions. Simultaneously they show the enormous increase in possibilities for flight maneuvers by being able to consider different and opposite mission objectives.

Keywords: deep space navigation, guidance, multi-objective, non-linear optimization, optimal control, trajectory planning.

Procedia PDF Downloads 412

Authors: A. Arshad, M. Lehtonen. M. Humayun

Abstract:

With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

Procedia PDF Downloads 312

Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

Abstract:

This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: building's energy, control system, energy management, energy storage, genetic optimization algorithm, greenhouse gases, modelling, renewable energy

Procedia PDF Downloads 257

Authors: Miriam Schäffer, Vinayak Mudgal, Wolfram Remlinger

Abstract:

The functions of automated driving will initially be limited to certain so-called Operating Driving Domains (ODD). Within the ODDs, the automated vehicle can handle all situations autonomously. In the event of a critical system failure, the vehicle will establish a condition of minimal risk or offer the driver to take over control of the vehicle. When the vehicle leaves the ODD, the driver is also prompted to take over vehicle control. During automated driving, the driver is legally allowed to perform non-driving-related activities (NDRAs) for the first time. When requested to take over, the driver must return from the NDRA state to a driving-ready state. The driver’s NDRA state may imply the use of items that are necessary for the NDRA or interior modifications. Since perceived comfort is an important factor in both manual and automated driving, a study was conducted in a static driving simulator to investigate factors that influence perceived comfort during the take-over process. Based on a literature review of factors influencing perceived comfort in different domains, selected parameters such as the TOR modality or elements to support handing over the item used for the NDRA to the interior were varied. Perceived comfort and discomfort were assessed using an adapted version of a standardized comfort questionnaire, as well as other previously identified aspects of comfort. The NDRA conducted was Using a Smartphone (playing Tetris) because of its high relevance as a future NDRA. The results show the potential to increase perceived comfort through interior adaptations and support elements. Further research should focus on different layouts of the investigated factors, as well as under different conditions, such as time budget, actions required within the intervention in the vehicle control system, and vehicle interior dimensions.

Keywords: automated driving, comfort, take-over, vehicle interior

Procedia PDF Downloads 22

Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

Abstract:

a systematic observation from a defined time of origin up to certain failure or censor is known as survival data. Survival analysis is a major area of interest in biostatistics and biomedical researches. At the heart of understanding, the most scientific and medical research inquiries lie for a causality analysis. Thus, the main concern of this study is to investigate the causal effect of treatment on survival time conditional to the possibly time-varying covariates. The theory of causality often differs from the simple association between the response variable and predictors. A causal estimation is a scientific concept to compare a pragmatic effect between two or more experimental arms. To evaluate an average treatment effect on survival outcome, the estimating equation was adjusted for time-varying covariates under the semi-parametric transformation models. The proposed model intuitively obtained the consistent estimators for unknown parameters and unspecified monotone transformation functions. In this article, the proposed method estimated an unbiased average causal effect of treatment on survival time of interest. The modified estimating equations of semiparametric transformation models have the advantage to include the time-varying effect in the model. Finally, the finite sample performance characteristics of the estimators proved through the simulation and Stanford heart transplant real data. To this end, the average effect of a treatment on survival time estimated after adjusting for biases raised due to the high correlation of the left-truncation and possibly time-varying covariates. The bias in covariates was restored, by estimating density function for left-truncation. Besides, to relax the independence assumption between failure time and truncation time, the model incorporated the left-truncation variable as a covariate. Moreover, the expectation-maximization (EM) algorithm iteratively obtained unknown parameters and unspecified monotone transformation functions. To summarize idea, the ratio of cumulative hazards functions between the treated and untreated experimental group has a sense of the average causal effect for the entire population.

Keywords: a modified estimation equation, causal effect, semiparametric transformation models, survival analysis, time-varying covariate

Procedia PDF Downloads 177

Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

Abstract:

Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

Procedia PDF Downloads 44

Authors: Caroline Mendes, Mary McNamara, Orla Howe

Abstract:

For chemotherapy, a drug delivery system should be able to specifically target cancer cells and deliver the therapeutic dose without affecting normal cells. Folate receptors (FR) can be considered key targets since they are commonly over-expressed in cancer cells and they are the molecular marker used in this study. Here, cyclodextrin (CD) has being studied as a vehicle for delivering the chemotherapeutic drug, methotrexate (MTX). CDs have the ability to form inclusion complexes, in which molecules of suitable dimensions are included within the CD cavity. In this study, β-CD has been modified using folic acid so as to specifically target the FR molecular marker. Thus, the system studied here for drug delivery consists of β-CD, folic acid and MTX (CDEnFA:MTX). Cellular uptake of folic acid is mediated with high affinity by folate receptors while the cellular uptake of antifolates, such as MTX, is mediated with high affinity by the reduced folate carriers (RFCs). This study addresses the gene (mRNA) and protein expression levels of FRs and RFCs in the cancer cell lines CaCo-2, SKOV-3, HeLa, MCF-7, A549 and the normal cell line BEAS-2B, quantified by real-time polymerase chain reaction (real-time PCR) and flow cytometry, respectively. From that, four cell lines with different levels of FRs, were chosen for cytotoxicity assays of MTX and CDEnFA:MTX using the MTT assay. Real-time PCR and flow cytometry data demonstrated that all cell lines ubiquitously express moderate levels of RFC. These experiments have also shown that levels of FR protein in CaCo-2 cells are high, while levels in SKOV-3, HeLa and MCF-7 cells are moderate. A549 and BEAS-2B cells express low levels of FR protein. FRs are highly expressed in all the cancer cell lines analysed when compared to the normal cell line BEAS-2B. The cell lines CaCo-2, MCF-7, A549 and BEAS-2B were used in the cell viability assays. 48 hours treatment with the free drug and the complex resulted in IC50 values of 93.9 µM ± 9.2 and 56.0 µM ± 4.0 for CaCo-2 for free MTX and CDEnFA:MTX respectively, 118.2 µM ± 10.8 and 97.8 µM ± 12.3 for MCF-7, 36.4 µM ± 6.9 and 75.0 µM ± 8.5 for A549 and 132.6 µM ± 12.1 and 288.1 µM ± 16.3 for BEAS-2B. These results demonstrate that MTX is more toxic towards cell lines expressing low levels of FR, such as the BEAS-2B. More importantly, these results demonstrate that the inclusion complex CDEnFA:MTX showed greater cytotoxicity than the free drug towards the high FR expressing CaCo-2 cells, indicating that it has potential to target this receptor, enhancing the specificity and the efficiency of the drug.

Keywords: cyclodextrins, cancer treatment, drug delivery, folate receptors, reduced folate carriers

Procedia PDF Downloads 302

Authors: Boguslaw Schreyer

Abstract:

In some types of wheeled robots it is important to secure starting acceleration and deceleration maxima while at the same time maintaining transversal stability. In this paper torque distribution between the front and rear wheels as well as the timing of torque application have been calculated. Both secure an optimum traction coefficient. This paper also identifies required input signals to a control unit, which controls the torque values and timing. Using a three dimensional, two mass model of a robot developed by the author a computer simulation was performed confirming the calculations presented in this paper. These calculations were also implemented and confirmed during military robot testing.

Keywords: robot dynamics, torque distribution, traction coefficient, wheeled robots

Procedia PDF Downloads 312

Authors: Tahsien Mohamed Okasha

Abstract:

Simulation is one of the emerging educational strategies that depend on the creation of scenarios to imitate what could happen in real life. At the time of COVID, we faced big obstacles in medical education, specially the clinical part and how we could apply it, the simulation was the golden key. Simulation is a very important tool of education for medical sector students, through creating a safe, changeable, quiet environment with less anxiety level for students to practice and to have repeated trials on their competencies. That impacts the level of practice, achievement, and the way of acting in real situations and experiences. A blind Random sample of students from different specialties and colleges who came and finished their training in an integrated environment was collected and tested, and the responses were graded from (1-5). The results revealed that 77% of the studied subjects agreed that dealing and interacting with different medical sector candidates in the same place was beneficial. 77% of the studied subjects agreed that simulations were challenging in thinking and decision-making skills .75% agreed that using high-fidelity manikins was helpful. 75% agree .76% agreed that working in a safe, prepared environment is helpful for realistic situations.

Keywords: simulation, clinical training, education, medical sector students

Procedia PDF Downloads 32

Authors: Morteza Pourazar, Fatemeh Mirakhori, Fazlolah Bagherzadeh, Rasool Hemayattalab

Abstract:

The purpose of study was to examine the effects of external and internal focus of attention in the motor learning of children with cerebral palsy. The study involved 30 boys (7 to 12 years old) with CP type 1 who practiced throwing beanbags. The participants were randomly assigned to the internal focus, external focus, and control groups, and performed six blocks of 10-trial with attentional focus reminders during a practice phase and no reminders during retention and transfer tests. Analysis of variance (ANOVA) with repeated measures on the last factor was used. The results show that significant main effects were found for time and group. However, the interaction of time and group was not significant. Retention scores were significantly higher for the external focus group. The external focus group performed better than other groups; however, the internal focus and control groups’ performance did not differ. The study concluded that motor skills in Spastic Hemiparetic Cerebral Palsy (SHCP) children could be enhanced by external attention.

Keywords: cerebral palsy, external attention, internal attention, throwing task

Procedia PDF Downloads 315

Authors: Bo Liu, Qingshan Kong, Weiqing Huang

Abstract:

With the rapid development of modern communication, diagnosing the fiber-optic quality and faults in real-time is widely focused. In this paper, a Labview-based system is proposed for fiber-optic faults detection. The wavelet threshold denoising method combined with Empirical Mode Decomposition (EMD) is applied to denoise the optical time domain reflectometer (OTDR) signal. Then the method based on Gabor representation is used to detect events. Experimental measurements show that signal to noise ratio (SNR) of the OTDR signal is improved by 1.34dB on average, compared with using the wavelet threshold denosing method. The proposed system has a high score in event detection capability and accuracy. The maximum detectable fiber length of the proposed Labview-based system can be 65km.

Keywords: empirical mode decomposition, events detection, Gabor transform, optical time domain reflectometer, wavelet threshold denoising

Procedia PDF Downloads 123

Authors: Y. Johnson

Abstract:

Study of multi-satellite formation flight systems has drawn wide attention recently due to so many potential advantages. The present work aims to model the relative motion dynamics in terms of change in classical orbital parameters between the two satellites-chief and deputy- under Earth’s oblateness effect. The required impulsive thrust control is calculated to minimize these orbital parameter changes. The formation configuration is initialized by selecting a set of orbital parameters for the chief and deputy satellites such that bounded motion is maintained for a long time in a J_2-invariant relative non-circular orbit between the satellites. The solution of J_2-modified Hill’s equations is also derived in this paper.

Keywords: satellite, formation flight, j2 effect, control

Procedia PDF Downloads 275

Authors: Ambrish Tiwari, Sudhasini Panda, Archana Singh, Kalpana Luthra, S. K. Sharma

Abstract:

Introduction: On the basis of available literature we know that various host factors play a role in outcome of Tuberculosis (TB) infection by modulating innate immunity. One such factor is Inducible Nitric Oxide Synthase enzyme (iNOS) which help in the production of Nitric Oxide (NO), an antimicrobial agent. Expression of iNOS is in control of various host factors in which Vitamin D along with its nuclear receptor Vitamin D receptor (VDR) is one of them. Vitamin D along with its receptor also produces cathelicidin (antimicrobicidal agent). With this background, we attempted to investigate the levels of Vitamin D and NO along with their associated molecules in tuberculosis patients and household contacts as compared to healthy controls and assess the implication of these findings in susceptibility to tuberculosis (TB). Study subjects and methods: 100 active TB patients, 75 household contacts, and 70 healthy controls were taken. VDR and iNOS mRNA levels were studied using real-time PCR. Serum VDR, cathelicidin, iNOS levels were measured using ELISA. Serum Vitamin D levels were measured in serum samples using chemiluminescence based immunoassay. NO was measured using colorimetry based kit. Results: VDR and iNOS mRNA levels were found to be lower in active TB group compared to household contacts and healthy controls (P=0.0001 and 0.005 respectively). The serum levels of Vitamin D were also found to be lower in active TB group as compared to healthy controls (P =0.001). Levels of cathelicidin and NO was higher in patient group as compared to other groups (p=0.01 and 0.5 respectively). However, the expression of VDR and iNOS and levels of vitamin D was significantly (P < 0.05) higher in household contacts compared to both active TB and healthy control groups. Inference: Higher levels of Vitamin D along with VDR and iNOS expression in household contacts as compared to patients suggest that vitamin D might have a protective role against TB which prevents activation of the disease. From our data, we can conclude that decreased vitamin D levels could be implicated in disease progression and we can use cathelicidin and NO as a biomarker for early diagnosis of pulmonary tuberculosis.

Keywords: vitamin D, VDR, iNOS, tuberculosis

Procedia PDF Downloads 304

Authors: Sule Sahin, Basak Bulut Karageyik

Abstract:

This paper introduces a hazard rate function for the time of ruin to calculate the conditional probability of ruin for very small intervals. We call this function the force of ruin (FoR). We obtain the expected time of ruin and conditional expected time of ruin from the exact finite time ruin probability with exponential claim amounts. Then we introduce the FoR which gives the conditional probability of ruin and the condition is that ruin has not occurred at time t. We analyse the behavior of the FoR function for different initial surpluses over a specific time interval. We also obtain FoR under the excess of loss reinsurance arrangement and examine the effect of reinsurance on the FoR.

Keywords: conditional time of ruin, finite time ruin probability, force of ruin, reinsurance

Procedia PDF Downloads 407

Authors: Gulshan Mammadova

Abstract:

This paper presents the results of studying the surface microrelief in 2D and 3D models and analyzing the spectroscopy of a three-junction TlInSe₂ crystal. Analysis of the results obtained showed that with a change in the composition of the TlInSe₂ crystal, sharp changes occur in the microrelief of its surface. An X-ray optical diffraction analysis of the TlInSe₂ crystal was experimentally carried out. Based on ellipsometric data, optical functions were determined - the real and imaginary parts of the dielectric permittivity of crystals, the coefficients of optical absorption and reflection, the dependence of energy losses and electric field power on the effective density, the spectral dependences of the real (σᵣ) and imaginary (σᵢ) parts, optical electrical conductivity were experimentally studied. The fluorescence spectra of the ternary compound TlInSe₂ were isolated and analyzed when excited by light with a wavelength of 532 nm. X-ray studies of TlInSe₂ showed that this phase crystallizes into tetragonal systems. Ellipsometric measurements showed that the real (ε₁) and imaginary (ε₂) parts of the dielectric constant are components of the dielectric constant tensor of the uniaxial joints under consideration and do not depend on the angle. Analysis of the dependence of the real and imaginary parts of the refractive index of the TlInSe₂ crystal on photon energy showed that the nature of the change in the real and imaginary parts of the dielectric constant does not differ significantly. When analyzing the spectral dependences of the real (σr) and imaginary (σi) parts of the optical electrical conductivity, it was noticed that the real part of the optical electrical conductivity increases exponentially in the energy range 0.894-3.505 eV. In the energy range of 0.654-2.91 eV, the imaginary part of the optical electrical conductivity increases linearly, reaches a maximum value, and decreases at an energy of 2.91 eV. At 3.6 eV, an inversion of the imaginary part of the optical electrical conductivity of the TlInSe₂ compound is observed. From the graphs of the effective power density versus electric field energy losses, it is known that the effective power density increases significantly in the energy range of 0.805–3.52 eV. The fluorescence spectrum of the ternary compound TlInSe₂ upon excitation with light with a wavelength of 532 nm has been studied and it has been established that this phase has luminescent properties.

Keywords: optical properties, dielectric permittivity, real and imaginary dielectric permittivity, optical electrical conductivity

Procedia PDF Downloads 63

Authors: Donghee Kang

Abstract:

Background: Cancer pain is very difficult to control as the mechanism of pain is varied, and the patient has several co-morbidities. The use of Intravenous Patient-Controlled Analgesia (IV-PCA) can effectively control underlying pain and breakthrough pain. Ketamine is used in many pain patients due to its unique analgesic effect. In this study, it was checked whether there was a difference in the amount of analgesic usage, pain control degree, and side effects between patients who controlled pain with fentanyl-based IV-PCA and those who added Ketamine for pain control. Methods: Among the patients referred to this department for cancer pain, IV-PCA was applied to patients who were taking sufficient oral analgesics but could not control them or had blood clotting disorders that made the procedure difficult, and this patient group was targeted. In IV-PCA, 3000 mcg of Fentanyl, 160 mg of Nefopam, and 0.3 mg of Ramosetrone were mixed with normal saline to make a total volume of 100 ml. Group F used this IV-PCA as it is, and group K mixed 250 mg of Ketamine with normal saline to make a total volume of 100 ml. For IV-PCA, the basal rate was 0.5ml/h, the bolus was set to 1ml when pressed once, and the lockout time was set to 15 minutes. If pain was not controlled after IV-PCA application, 500 mcg of Fentanyl was added, and if excessive sedation or breathing difficulties occurred, the use was stopped for one hour. After that, the degree of daily pain control, analgesic usage, and side effects were investigated for seven days using this IV-PCA. Results: There was no difference between the two groups in the demographic data. Both groups had adequate pain control. Initial morphine milligram equivalents did not differ between the two groups, but the total amount of Fentanyl used for seven days was significantly different between the two groups [p=0.014], and group F used more Fentanyl through IV-PCA. In addition, the amount of sleeping pills used during the seven days was higher in Group F [p<0.01]. Overall, there was no difference in the frequency of side effects between the two groups, but the nausea was more frequent in Group F [p=0.031]. Discussion: When the two groups were compared, pain control was good in both groups. This seems to be because Fentanyl-based IV-PCA showed an adequate pain control effect. However, there was a significant difference in the total amount of opioid (Fentanyl) used, which is thought to be the opioid-sparing effect of Ketamine. Also, among the side effects, nausea was significantly less, which is thought to be possible because the amount of opioids used in the Ketamine group was small. The frequency of requesting sleeping pills was significantly less in the group using Ketamine, and it seems that Ketamine also helped improve sleep quality. In conclusion, using Ketamine with an opioid to control pain seems to have advantages. IV-PCA, which can be used effectively when other procedures are difficult, is more effective and safer when used together with Ketamine than opioids alone.

Keywords: cancer pain, intravenous patient-controlled analgesia, Ketamine, opioid

Procedia PDF Downloads 82

Authors: Kréhi Serge Agbli, Samuel Portebos, Michaël Salomon

Abstract:

Here a methodology is considered aiming at evaluating the economic benefit of the provision of a primary frequency control unit using a Battery Energy Storage System (BESS). In this methodology, two control types (basic and hysteresis) are implemented and the corresponding minimum energy storage system power allowing to maintain the frequency drop inside a given threshold under a given contingency is identified and compared using DigSilent’s PowerFactory software. Following this step, the corresponding energy storage capacity (in MWh) is calculated. As PowerFactory is dedicated to dynamic simulation for transient analysis, a first order model related to the IEEE 9 bus grid used for the analysis under PowerFactory is characterized and implemented on MATLAB-Simulink. Primary frequency control is simulated using the two control types over one-month grid's frequency deviation data on this Simulink model. This simulation results in the energy throughput both basic and hysteresis BESSs. It emerges that the 15 minutes operation band of the battery capacity allocated to frequency control is sufficient under the considered disturbances. A sensitivity analysis on the width of the control deadband is then performed for the two control types. The deadband width variation leads to an identical sizing with the hysteresis control showing a better frequency control at the cost of a higher delivered throughput compared to the basic control. An economic analysis comparing the cost of the sized BESS to the potential revenues is then performed.

Keywords: battery energy storage system, electrical network frequency stability, frequency control unit, PowerFactor

Procedia PDF Downloads 130

Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

Abstract:

What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

Procedia PDF Downloads 239

Authors: Rebecca Richards Steed, James Van Derslice, Ken Smith, Richard Medina, Amanda Bakian

Abstract:

Elucidating gene-environment interactions for heritable disease outcomes is an emerging area of disease research, with genetic studies informing hypotheses for environment and gene interactions underlying some of the most confounding diseases of our time, like autism spectrum disorder (ASD). Geography has thus far played a key role in identifying environmental factors contributing to disease, but its use can be broadened to include genetic and environmental factors that have a synergistic effect on disease. Through the use of family pedigrees and disease outcomes with life-course residential histories, space-time clustering of generations at critical developmental windows can provide further understanding of (1) environmental factors that contribute to disease patterns in families, (2) susceptible critical windows of development most impacted by environment, (3) and that are most likely to lead to an ASD diagnosis. This paper introduces a retrospective case-control study that utilizes pedigree data, health data, and residential life-course location points to find space-time clustering of ancestors with a grandchild/child with a clinical diagnosis of ASD. Finding space-time clusters of ancestors at critical developmental windows serves as a proxy for shared environmental exposures. The authors refer to geographic life-course exposures as geographic legacies. Identifying space-time clusters of ancestors creates a bridge for researching exposures of past generations that may impact modern-day progeny health. Results from the space-time cluster analysis show multiple clusters for the maternal and paternal pedigrees. The paternal grandparent pedigree resulted in the most space-time clustering for birth and childhood developmental windows. No statistically significant clustering was found for adolescent years. These results will be further studied to identify the specific share of space-time environmental exposures. In conclusion, this study has found significant space-time clusters of parents, and grandparents for both maternal and paternal lineage. These results will be used to identify what environmental exposures have been shared with family members at critical developmental windows of time, and additional analysis will be applied.

Keywords: family pedigree, environmental exposure, geographic legacy, medical geography, transgenerational inheritance

Procedia PDF Downloads 117

Authors: Espen Oland

Abstract:

This paper presents a solution to the problem of autonomous rendezvous for spacecraft equipped with one main thruster for translational control and three reaction wheels for rotational control. With fewer actuators than degrees of freedom, this constitutes an underactuated control problem, requiring a coupling between the translational and rotational dynamics to facilitate control. This paper shows how to obtain this coupling, and applies the results to autonomous rendezvous between a follower spacecraft and a leader spacecraft. Additionally, since the thrust is constrained between zero and an upper bound, no negative forces can be generated to slow down the speed of the spacecraft. A combined speed and attitude control logic is therefore created that can be divided into three main phases: 1) The orbital velocity vector is pointed towards the desired position and the thrust is used to obtain the desired speed, 2) during the coasting phase, the attitude is changed to facilitate deceleration using the main thruster, 3) the speed is decreased as the spacecraft reaches its desired position. The results are validated through simulations, showing the capabilities of the proposed approach.

Keywords: attitude control, spacecraft rendezvous, translational control, underactuated rigid body

Procedia PDF Downloads 293

Authors: Oluwaseun Simon Adekanle, M'hammed Guisser, Elhassane Abdelmounim, Mohamed Aboulfatah

Abstract:

In this paper, modeling and control of a grid connected 660KW Doubly-Fed Induction Generator wind turbine is presented. Stator flux orientation is used to realize active-reactive power decoupling to enable independent control of active and reactive power. The recursive Integral Backstepping technique is used to control generator speed to its optimum value and to obtain unity power factor. The controller is combined with High Gain Observer to estimate the mechanical torque of the machine. The most important advantage of this combination of High Gain Observer and the Integral Backstepping controller is the annulation of static error that may occur due to incertitude between the actual value of a parameter and its estimated value by the controller. Simulation results under Matlab/Simulink show the robustness of this control technique in presence of parameter variation.

Keywords: doubly-fed induction generator, field orientation control, high gain observer, integral backstepping control

Procedia PDF Downloads 363

Authors: Anca Dinischiotu, Sorina Nicoleta Voicu

Abstract:

Silica nanoparticles (SiO2-NPs) are widely used in consumer products such as paints, plastics, insulation materials, tires, concrete production, as well as in gene delivery systems and imaging procedures. Environmental human exposure to them occurs during utilization of these products, in a time-dependent manner, the uptake being by topic and inhalation route especially. SiO2-NPs enter cells and induce membrane damage, oxidative stress and inflammatory reactions in a concentration-dependent manner. In this study, MRC-5 cells (human fetal lung fibroblasts) were exposed to amorphous SiO2-NPs at a dose of 62.5 μg/ml for 24, 48 and 72 hours. The size distribution of NPs was a lognormal function, in the range 3-14 nm. A time-dependent decrease of total reduced glutathione concentration by 36%, 50%, and 78% and an increase of NO level by 62%, 32%, respectively 24% compared to control were noticed. An up-regulation of NF-kB expression by 20%, 50% respectively 10% and of Nrf-2 by 139%, 58%, and 16% compared to control after 24, 48 and 72 hours was noticed also. The expression of IL-1β, IL-6, IL-8, and COX-2 was up-regulated in a time-dependent manner. Also, the expression of MMP-2 and MMP-9 were down-regulated after 48 and 72 hours, whereas their activities raised in a time-dependent manner. Exposure of cells to NPs up-regulated the expression of inducible NO synthase, as previously was shown, and probably this is the reason for the increased level of NO, that can react with the thiol groups of reduced glutathione molecules, diminishing its concentration Nrf2 is a transcription factor translocated in nucleus, under oxidative stress, where downstream gene expression activates in order to modulate the adaptive intracellular response against oxidative stress. The cross-talk between Nrf2 and NF-kB activities regulates the inflammatory processes. The activation of NF-kB could activate up-regulation of IL-1β, IL-6, and IL-8. The increase of COX-2 expression could be correlated with IL-1β one. Also, probably in response to the pro-inflammatory cytokines, MMP-2 and MMP-9 were induced and activated. In conclusion, the exposure of MRC-5 cells to SiO2-NPs generated inflammation in a time-dependent manner.

Keywords: inflammation, MRC-5 cells, oxidative stress, silica nanoparticles

Procedia PDF Downloads 147

Authors: Oznur Ispir, S. Duygulu

Abstract:

Health institutions are the places where fast and efficient decisions are required and mistakes and uncertainties are not tolerated due to the urgency of the services provided within the body of these institutions. Thus, in those institutions where patient care services are targeted to be provided quality and safety, the nurses attending the decisions, creating the solutions for problems, taking initiative and bearing the responsibility of results in brief having the control over practices are needed. Control over nursing practices is defined as affecting the employment and work environment at the unit level of the institution, perceived freedom for organizing and evaluating nursing practices, the ability to make independent decisions about patient care and accountability for the results of such decisions. This study scrutinizes the concept of control over nursing practices (organizational autonomy), which is frequently confused with other concepts (autonomy) in the literature, by reviewing the literature and making suggestions to improve nurses’ control over nursing practices.

Keywords: control over nursing practice, nurse, nursing, organizational autonomy

Procedia PDF Downloads 268

Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

Abstract:

The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

Procedia PDF Downloads 324

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

Procedia PDF Downloads 379

Authors: Ali Kazemi

Abstract:

The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

Procedia PDF Downloads 59

Authors: Maria Ahmadnezhad, Seyedgharani Ghoreishi ‎

Abstract:

Electrohydraulic servo system have been used in industry in a wide ‎number of applications. Its ‎dynamics are highly nonlinear and also ‎have large extent of model uncertainties and external ‎disturbances. ‎In this thesis, a robust back-stepping control (RBSC) scheme is ‎proposed to overcome ‎the problem of disturbances and system ‎uncertainties effectively and to improve the set-point ‎performance ‎of EHS systems. In order to implement the proposed control ‎scheme, the system ‎uncertainties in EHS systems are considered as ‎total leakage coefficient and effective oil volume. In ‎addition, in ‎order to obtain the virtual controls for stabilizing system, the ‎update rule for the ‎system uncertainty term is induced by the ‎Lyapunov control function (LCF). To verify the ‎performance and ‎robustness of the proposed control system, computer simulation of ‎the ‎proposed control system using Matlab/Simulink Software is ‎executed. From the computer ‎simulation, it was found that the ‎RBSC system produces the desired set-point performance and ‎has ‎robustness to the disturbances and system uncertainties of ‎EHS systems.‎

Keywords: electro hydraulic servo system, back-stepping control, robust back-‎stepping control, Lyapunov redesign‎

Procedia PDF Downloads 1004

Authors: Khaled Mohammed

Abstract:

This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

Procedia PDF Downloads 155

Authors: Taha Enes Kon, Vanshika Reddy

Abstract:

This project focuses on developing a gamified mobile application to aid in stroke rehabilitation by enhancing motor skills through interactive activities. The primary goal was to design a companion app for a passive haptic rehab glove, incorporating Google MediaPipe for gesture tracking and vibrotactile feedback. The app simulates farming activities, offering a fun and engaging experience while addressing the monotony of traditional rehabilitation methods. The prototype focuses on a single minigame, Flower Picking, which uses gesture recognition to interact with virtual elements, encouraging users to perform exercises that improve hand dexterity. The development process involved creating accessible and user-centered designs using Figma, integrating gesture recognition algorithms, and implementing unity-based game mechanics. Real-time feedback and progressive difficulty levels ensured a personalized experience, motivating users to adhere to rehabilitation routines. The prototype achieved a gesture detection precision of 90%, effectively recognizing predefined gestures such as the Fist and OK symbols. Quantitative analysis highlighted a 40% increase in average session duration compared to traditional exercises, while qualitative feedback praised the app’s immersive design and ease of use. Despite its success, challenges included rigidity in gesture recognition, requiring precise hand orientations, and limited gesture support. Future improvements include expanding gesture adaptability and incorporating additional minigames to target a broader range of exercises. The project demonstrates the potential of gamification in stroke rehabilitation, offering a scalable and accessible solution that complements clinical treatments, making recovery engaging and effective for users.

Keywords: stroke rehabilitation, haptic feedback, gamification, MediaPipe, motor control

Procedia PDF Downloads 7