Search results for: acceleration overload signal
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2258

Search results for: acceleration overload signal

1628 Green Wave Control Strategy for Optimal Energy Consumption by Model Predictive Control in Electric Vehicles

Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

Abstract:

Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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1627 Comparative Study of Equivalent Linear and Non-Linear Ground Response Analysis for Rapar District of Kutch, India

Authors: Kulin Dave, Kapil Mohan

Abstract:

Earthquakes are considered to be the most destructive rapid-onset disasters human beings are exposed to. The amount of loss it brings in is sufficient to take careful considerations for designing of structures and facilities. Seismic Hazard Analysis is one such tool which can be used for earthquake resistant design. Ground Response Analysis is one of the most crucial and decisive steps for seismic hazard analysis. Rapar district of Kutch, Gujarat falls in Zone 5 of earthquake zone map of India and thus has high seismicity because of which it is selected for analysis. In total 8 bore-log data were studied at different locations in and around Rapar district. Different soil engineering properties were analyzed and relevant empirical correlations were used to calculate maximum shear modulus (Gmax) and shear wave velocity (Vs) for the soil layers. The soil was modeled using Pressure-Dependent Modified Kodner Zelasko (MKZ) model and the reference curve used for fitting was Seed and Idriss (1970) for sand and Darendeli (2001) for clay. Both Equivalent linear (EL), as well as Non-linear (NL) ground response analysis, has been carried out with Masing Hysteretic Re/Unloading formulation for comparison. Commercially available DEEPSOIL v. 7.0 software is used for this analysis. In this study an attempt is made to quantify ground response regarding generated acceleration time-history at top of the soil column, Response spectra calculation at 5 % damping and Fourier amplitude spectrum calculation. Moreover, the variation of Peak Ground Acceleration (PGA), Maximum Displacement, Maximum Strain (in %), Maximum Stress Ratio, Mobilized Shear Stress with depth is also calculated. From the study, PGA values estimated in rocky strata are nearly same as bedrock motion and marginal amplification is observed in sandy silt and silty clays by both analyses. The NL analysis gives conservative results of maximum displacement as compared to EL analysis. Maximum strain predicted by both studies is very close to each other. And overall NL analysis is more efficient and realistic because it follows the actual hyperbolic stress-strain relationship, considers stiffness degradation and mobilizes stresses generated due to pore water pressure.

Keywords: DEEPSOIL v 7.0, ground response analysis, pressure-dependent modified Kodner Zelasko model, MKZ model, response spectra, shear wave velocity

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1626 A Comparison of Alternative Traffic Controls for Interchange Ramp Areas Using Synchro Software

Authors: Mohamed Mesbah, Bruce Janson

Abstract:

An interchange is the most important component of freeway and highway facilities. It is working as a connector between the highway’s elements. The main goal of designing interchanges is to provide an acceptable level of service and delay to make vehicles move smoothly when they are entering and exiting the interchange. There are many factors that can have a significant impact on the level of service; the main factors are traffic volumes, and type of interchange. This paper will discuss interchange with roundabouts under various values of traffic volumes to determine the level of service of the interchanges that will be studied in this paper and replace the system of interchange from roundabout to traffic signal to make a significant compression between these systems. A secondary goal is to propose improvements for scenarios where the level of service is deemed unacceptable. This will be achieved using Synchro traffic simulation software, which facilitates the simulation and optimization of interchanges to enhance operational efficiency and safety.

Keywords: interchange, roundabout, traffic signal, Synchro, delay, level of service, traffic volumes, vehicles, simulation, optimization, adjustment

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1625 Nanorods Based Dielectrophoresis for Protein Concentration and Immunoassay

Authors: Zhen Cao, Yu Zhu, Junxue Fu

Abstract:

Immunoassay, i.e., antigen-antibody reaction, is crucial for disease diagnostics. To achieve the adequate signal of the antigen protein detection, a large amount of sample and long incubation time is needed. However, the amount of protein is usually small at the early stage, which makes it difficult to detect. Unlike cells and DNAs, no valid chemical method exists for protein amplification. Thus, an alternative way to improve the signal is through particle manipulation techniques to concentrate proteins, among which dielectrophoresis (DEP) is an effective one. DEP is a technique that concentrates particles to the designated region through a force created by the gradient in a non-uniform electric field. Since DEP force is proportional to the cube of particle size and square of electric field gradient, it is relatively easy to capture larger particles such as cells. For smaller ones like proteins, a super high gradient is then required. In this work, three-dimensional Ag/SiO2 nanorods arrays, fabricated by an easy physical vapor deposition technique called as oblique angle deposition, have been integrated with a DEP device and created the field gradient as high as of 2.6×10²⁴ V²/m³. The nanorods based DEP device is able to enrich bovine serum albumin (BSA) protein by 1800-fold and the rate has reached 180-fold/s when only applying 5 V electric potential. Based on the above nanorods integrated DEP platform, an immunoassay of mouse immunoglobulin G (IgG) proteins has been performed. Briefly, specific antibodies are immobilized onto nanorods, then IgG proteins are concentrated and captured, and finally, the signal from fluorescence-labelled antibodies are detected. The limit of detection (LoD) is measured as 275.3 fg/mL (~1.8 fM), which is a 20,000-fold enhancement compared with identical assays performed on blank glass plates. Further, prostate-specific antigen (PSA), which is a cancer biomarker for diagnosis of prostate cancer after radical prostatectomy, is also quantified with a LoD as low as 2.6 pg/mL. The time to signal saturation has been significantly reduced to one minute. In summary, together with an easy nanorod fabrication and integration method, this nanorods based DEP platform has demonstrated highly sensitive immunoassay performance and thus poses great potentials in applications for early point-of-care diagnostics.

Keywords: dielectrophoresis, immunoassay, oblique angle deposition, protein concentration

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1624 Prediction of Sepsis Illness from Patients Vital Signs Using Long Short-Term Memory Network and Dynamic Analysis

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

Abstract:

The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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1623 Nonlinear Homogenized Continuum Approach for Determining Peak Horizontal Floor Acceleration of Old Masonry Buildings

Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

Abstract:

It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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1622 Electromyographic Analysis of Biceps Brachii during Golf Swing and Review of Its Impact on Return to Play Following Tendon Surgery

Authors: Amin Masoumiganjgah, Luke Salmon, Julianne Burnton, Fahimeh Bagheri, Gavin Lenton, S. L. Ezekial Tan

Abstract:

Introduction: The incidence of proximal biceps tenodesis and acute distal biceps repair is increasing, and rehabilitation protocols following both are variable. Golf is a popular sport within Australia, and the Gold Coast has become a Mecca for golfers, with more courses per capita than anywhere else in the world. Currently, there are no clear guidelines regarding return to golf play following biceps procedures. The aim of this study was to determine biceps brachii activation during the golf swing through electromyographic analysis, and subsequently, aid in rehabilitation guidelines and return to golf following tenodesis and repair. Methods: Subjects were amateur golfers with no previous upper limb surgery. Surface electromyography (EMG) and high-speed video recording were used to analyse activation of the left and right biceps brachii and the anterior deltoid during the golf swing. Each participant’s maximum voluntary contraction (MVC) was recorded, and they were then required to hit a golf ball aiming for specific distances of 2, 50, 100 and 150 metres at a driving range. Noraxon myoResearch and Matlab were used for data analysis. Mean % MVC was calculated for leading and trailing arms during the full swing and its’ 4 phases: back-swing, acceleration, early follow-through and late follow-through. Results: 12 golfers (2 female and 10 male), participated in the study. Median age was 27 (25 – 38), with all being right handed. Over all distances, the mean activation of the short and long head of biceps brachii was < 10% through the full swing. When breaking down the 50, 100 and 150m swing into phases, mean MVC activation was lowest in backswing (5.1%), followed by acceleration (9.7%), early follow-through (9.2%), and late follow-through (21.4%). There was more variation and slightly higher activation in the right biceps (trailing arm) in backswing, acceleration, and early follow-through; with higher activation in the leading arm in late follow-through (25.4% leading, 17.3% trailing). 2m putts resulted in low MVC values (3.1% ) with little variation across swing phases. There was considerable individual variation in results – one tense subject averaged 11.0% biceps MVC through the 2m putting stroke and others recorded peak mean MVC biceps activations of 68.9% at 50m, 101.3% at 100m, and 111.3% at 150m. Discussion: Previous studies have investigated the role of rotator cuff, spine, and hip muscles during the golf swing however, to our knowledge, this is the first study that investigates the activation of biceps brachii. Many rehabilitation programs following a biceps tenodesis or repair allow active range against gravity and restrict strengthening exercises until 6 weeks, and this does not appear to be associated with any adverse outcome. Previous studies demonstrate a range of < 10% MVC is similar to the unloaded biceps brachii during walking(1), active elbow flexion with the hand positioned either in pronation or supination will produce MVC < 20% throughout range(2) and elbow flexion with a 4kg dumbbell can produce mean MVC’s of around 40%(3). Our study demonstrates that increasing activation is associated with the leading arm, increasing shot distance and the late follow-through phase. Although the cohort mean MVC of the biceps brachii is <10% through the full swing, variability is high and biceps activation reach peak mean MVC’s of over 100% in different swing phases for some individuals. Given these EMG values, caution is advised when advising patients post biceps procedures to return to long distance golf shots, particularly when the leading arm is involved. Even though it would appear that putting would be as safe as having an unloaded hand out of a sling following biceps procedures, the variability of activation patterns across different golfers would lead us to caution against accelerated golf rehabilitation in those who may be particularly tense golfers. The 50m short iron shot was too long to consider as a chip shot and more work can be done in this area to determine the safety of chipping.

Keywords: electromyographic analysis, biceps brachii rupture, golf swing, tendon surgery

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1621 Effect of Traffic Composition on Delay and Saturation Flow at Signal Controlled Intersections

Authors: Arpita Saha, Apoorv Jain, Satish Chandra, Indrajit Ghosh

Abstract:

Level of service at a signal controlled intersection is directly measured from the delay. Similarly, saturation flow rate is a fundamental parameter to measure the intersection capacity. The present study calculates vehicle arrival rate, departure rate, and queue length for every five seconds interval in each cycle. Based on the queue lengths, the total delay of the cycle has been calculated using Simpson’s 1/3rd rule. Saturation flow has been estimated in terms of veh/hr of green/lane for every five seconds interval of the green period until at least three vehicles are left to cross the stop line. Vehicle composition shows an immense effect on total delay and saturation flow rate. The increase in two-wheeler proportion increases the saturation flow rate and reduces the total delay per vehicle significantly. Additionally, an increase in the heavy vehicle proportion reduces the saturation flow rate and increases the total delay for each vehicle.

Keywords: delay, saturation flow, signalised intersection, vehicle composition

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1620 A Novel PWM/PFM Controller for PSR Fly-Back Converter Using a New Peak Sensing Technique

Authors: Sanguk Nam, Van Ha Nguyen, Hanjung Song

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For low-power applications such as adapters for portable devices and USB chargers, the primary side regulation (PSR) fly-back converter is widely used in lieu of the conventional fly-back converter using opto-coupler because of its simpler structure and lower cost. In the literature, there has been studies focusing on the design of PSR circuit; however, the conventional sensing method in PSR circuit using RC delay has a lower accuracy as compared to the conventional fly-back converter using opto-coupler. In this paper, we propose a novel PWM/PFM controller using new sensing technique for the PSR fly-back converter which can control an accurate output voltage. The conventional PSR circuit can sense the output voltage information from the auxiliary winding to regulate the duty cycle of the clock that control the output voltage. In the sensing signal waveform, there has two transient points at time the voltage equals to Vout+VD and Vout, respectively. In other to sense the output voltage, the PSR circuit must detect the time at which the current of the diode at the output equals to zero. In the conventional PSR flyback-converter, the sensing signal at this time has a non-sharp-negative slope that might cause a difficulty in detecting the output voltage information since a delay of sensing signal or switching clock may exist which brings out an unstable operation of PSR fly-back converter. In this paper instead of detecting output voltage at a non-sharp-negative slope, a sharp-positive slope is used to sense the proper information of the output voltage. The proposed PRS circuit consists of a saw-tooth generator, a summing circuit, a sample and hold circuit and a peak detector. Besides, there is also the start-up circuit which protects the chip from high surge current when the converter is turned on. Additionally, to reduce the standby power loss, a second mode which operates in a low frequency is designed beside the main mode at high frequency. In general, the operation of the proposed PSR circuit can be summarized as following: At the time the output information is sensed from the auxiliary winding, a saw-tooth signal from the saw-tooth generator is generated. Then, both of these signals are summed using a summing circuit. After this process, the slope of the peak of the sensing signal at the time diode current is zero becomes positive and sharp that make the peak easy to detect. The output of the summing circuit then is fed into a peak detector and the sample and hold circuit; hence, the output voltage can be properly sensed. By this way, we can sense more accurate output voltage information and extend margin even circuit is delayed or even there is the existence of noise by using only a simple circuit structure as compared with conventional circuits while the performance can be sufficiently enhanced. Circuit verification was carried out using 0.35μm 700V Magnachip process. The simulation result of sensing signal shows a maximum error of 5mV under various load and line conditions which means the operation of the converter is stable. As compared to the conventional circuit, we achieved very small error only used analog circuits compare with conventional circuits. In this paper, a PWM/PFM controller using a simple and effective sensing method for PSR fly-back converter has been presented in this paper. The circuit structure is simple as compared with the conventional designs. The gained results from simulation confirmed the idea of the design

Keywords: primary side regulation, PSR, sensing technique, peak detector, PWM/PFM control, fly-back converter

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1619 Hypersonic Propulsion Requirements for Sustained Hypersonic Flight for Air Transportation

Authors: James Rate, Apostolos Pesiridis

Abstract:

In this paper, the propulsion requirements required to achieve sustained hypersonic flight for commercial air transportation are evaluated. In addition, a design methodology is developed and used to determine the propulsive capabilities of both ramjet and scramjet engines. Twelve configurations are proposed for hypersonic flight using varying combinations of turbojet, turbofan, ramjet and scramjet engines. The optimal configuration was determined based on how well each of the configurations met the projected requirements for hypersonic commercial transport. The configurations were separated into four sub-configurations each comprising of three unique derivations. The first sub-configuration comprised four afterburning turbojets and either one or two ramjets idealised for Mach 5 cruise. The number of ramjets required was dependent on the thrust required to accelerate the vehicle from a speed where the turbojets cut out to Mach 5 cruise. The second comprised four afterburning turbojets and either one or two scramjets, similar to the first configuration. The third used four turbojets, one scramjet and one ramjet to aid acceleration from Mach 3 to Mach 5. The fourth configuration was the same as the third, but instead of turbojets, it implemented turbofan engines for the preliminary acceleration of the vehicle. From calculations which determined the fuel consumption at incremental Mach numbers this paper found that the ideal solution would require four turbojet engines and two Scramjet engines. The ideal mission profile was determined as being an 8000km sortie based on an averaging of popular long haul flights with strong business ties, which included Los Angeles to Tokyo, London to New York and Dubai to Beijing. This paper deemed that these routes would benefit from hypersonic transport links based on the previously mentioned factors. This paper has found that this configuration would be sufficient for the 8000km flight to be completed in approximately two and a half hours and would consume less fuel than Concord in doing so. However, this propulsion configuration still result in a greater fuel cost than a conventional passenger. In this regard, this investigation contributes towards the specification of the engine requirements throughout a mission profile for a hypersonic passenger vehicle. A number of assumptions have had to be made for this theoretical approach but the authors believe that this investigation lays the groundwork for appropriate framing of the propulsion requirements for sustained hypersonic flight for commercial air transportation. Despite this, it does serve as a crucial step in the development of the propulsion systems required for hypersonic commercial air transportation. This paper provides a methodology and a focus for the development of the propulsion systems that would be required for sustained hypersonic flight for commercial air transportation.

Keywords: hypersonic, ramjet, propulsion, Scramjet, Turbojet, turbofan

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1618 The Strategies to Improve the Pedestrian System in the Context of Old Aging

Authors: Yuxiao Jiang, Dong Ma, Mengyu Zhan, Yingxia Yun

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China now is entering the phase of old aging and the aging speed is on acceleration. The proportion of the aged citizens in the urban areas is getting larger. Traveling on foot is one of the main travel methods for the old, but the bad walking environment and unsystematic pedestrian system cause inconvenience to the old who travel on foot. The paper analyzes the behavioral characteristics and the spatial preferences of the elderly group as well as the new traffic demands of them, finding out that some problems exist in the current pedestrian system. Thus, the paper proposes strategies in the areas of planning and design, and engineering technology so as to promote the traffic environment and perfect the pedestrian system for the old people.

Keywords: old aging, pedestrian system, perfection strategies, travel characteristics, future demand

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1617 A Novel RLS Based Adaptive Filtering Method for Speech Enhancement

Authors: Pogula Rakesh, T. Kishore Kumar

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Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss

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1616 The Non-Linear Analysis of Brain Response to Visual Stimuli

Authors: H. Namazi, H. T. N. Kuan

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Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes.

Keywords: visual stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

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1615 The New Economy: A Pedagogy for Vocational and Technical Education Programmes in Nigeria

Authors: Sunny Nwakanma

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The emergence of the new economy has created a new world order for skill acquisition, economic activities and employment. It has dramatically changed the way we live, learn, work and even think about work. It has also created new opportunities as well as challenges and uncertainty. This paper will not only demystify the new economy and present its instrumentality in the acceleration of skill acquisition in technical education, but will also highlight industrial and occupational changes brought about by the synergy between information and communication technology revolution and the global economic system. It advocates among other things, the use of information and communication technology mediated instruction in technical education as it provides the flexibility to meet diverse learners’ need anytime and anywhere and facilitate skill acquisition.

Keywords: new economy, technical education, skill acquisition, information and communication technology

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1614 New Suspension Mechanism for a Formula Car using Camber Thrust

Authors: Shinji Kajiwara

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The basic ability of a vehicle is the ability to “run”, “turn” and “stop”. The safeness and comfort during a drive on various road surfaces and speed depends on the performance of these basic abilities of the vehicle. Stability and maneuverability of a vehicle is vital in automotive engineering. Stability of a vehicle is the ability of the vehicle to revert back to a stable state during a drive when faced with crosswind and irregular road conditions. Maneuverability of a vehicle is the ability of the vehicle to change direction during a drive swiftly based on the steering of the driver. The stability and maneuverability of a vehicle can also be defined as the driving stability of the vehicle. Since fossil fueled vehicle is the main type of transportation today, the environmental factor in automotive engineering is also vital. By improving the fuel efficiency of the vehicle, the overall carbon emission will be reduced thus reducing the effect of global warming and greenhouse gas on the Earth. Another main focus of the automotive engineering is the safety performance of the vehicle especially with the worrying increase of vehicle collision every day. With better safety performance on a vehicle, every driver will be more confidence driving every day. Next, let us focus on the “turn” ability of a vehicle. By improving this particular ability of the vehicle, the cornering limit of the vehicle can be improved thus increasing the stability and maneuverability factor. In order to improve the cornering limit of the vehicle, a study to find the balance between the steering systems, the stability of the vehicle, higher lateral acceleration and the cornering limit detection must be conducted. The aim of this research is to study and develop a new suspension system that that will boost the lateral acceleration of the vehicle and ultimately improving the cornering limit of the vehicle. This research will also study environmental factor and the stability factor of the new suspension system. The double wishbone suspension system is widely used in four-wheel vehicle especially for high cornering performance sports car and racing car. The double wishbone designs allow the engineer to carefully control the motion of the wheel by controlling such parameters as camber angle, caster angle, toe pattern, roll center height, scrub radius, scuff and more. The development of the new suspension system will focus on the ability of the new suspension system to optimize the camber control and to improve the camber limit during a cornering motion. The research will be carried out using the CAE analysis tool. Using this analysis tool we will develop a JSAE Formula Machine equipped with the double wishbone system and also the new suspension system and conduct simulation and conduct studies on performance of both suspension systems.

Keywords: automobile, camber thrust, cornering force, suspension

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1613 Artificial Intelligence for Traffic Signal Control and Data Collection

Authors: Reggie Chandra

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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

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1612 Cooperative Diversity Scheme Based on MIMO-OFDM in Small Cell Network

Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

Procedia PDF Downloads 508
1611 New Concept for Real Time Selective Harmonics Elimination Based on Lagrange Interpolation Polynomials

Authors: B. Makhlouf, O. Bouchhida, M. Nibouche, K. Laidi

Abstract:

A variety of methods for selective harmonics elimination pulse width modulation have been developed, the most frequently used for real-time implementation based on look-up tables method. To address real-time requirements based in modified carrier signal is proposed in the presented work, with a general formulation to real-time harmonics control/elimination in switched inverters. Firstly, the proposed method has been demonstrated for a single value of the modulation index. However, in reality, this parameter is variable as a consequence of the voltage (amplitude) variability. In this context, a simple interpolation method for calculating the modified sine carrier signal is proposed. The method allows a continuous adjustment in both amplitude and frequency of the fundamental. To assess the performance of the proposed method, software simulations and hardware experiments have been carried out in the case of a single-phase inverter. Obtained results are very satisfactory.

Keywords: harmonic elimination, Particle Swarm Optimisation (PSO), polynomial interpolation, pulse width modulation, real-time harmonics control, voltage inverter

Procedia PDF Downloads 506
1610 Electrochemiluminescent Detection of DNA Damage Induced by Tetrachloro-1,4- Benzoquinone Using DNA Sensor

Authors: Tian-Fang Kang, Xue Sun

Abstract:

DNA damage induced by tetrachloro-1,4-benzoquinone (TCBQ), a reactive metabolite of pentachloro-phenol (PCP), was investigated using a glassy carbon electrode (GCE) modified with calf thymus double-stranded DNA (ds-DNA) in this work. DNA modified films were constructed by layer-by-layer adsorption of polycationic poly(diallyldimethyl- ammonium chloride) (PDDA) and negatively charged ds-DNA on the surface of a glassy carbon electrode. The DNA intercalator [Ru(bpy)2(dppz)]2+ (bpy=2, 2′-bipyridine, dppz0dipyrido [3, 2-a: 2′,3′-c] phenazine) was chosen as an electrochemical probe to detect DNA damage. After the sensor was incubated in 0.1 M pH 7.3 phosphate buffer solution (PBS) for 30min, the intact PDDA/DNA film produced a sensitive electrochemiluminescent (ECL) signal. However, after the sensor was incubated in 100 μM TCBQ or a mixed solution of 100 μM TCBQ and 2 mM H2O2, ECL signal decreased significantly. During the incubation of DNA in TCBQ or TCBQ-H2O2 solution, the double-helix of DNA was damaged, which resulted in the decrease of Ru-dppz bound to DNA. Additionally, the results were verified independently by fluorescence experiments. This paper provides a sensitive method to directly screen DNA damage induced by chemicals in the environment.

Keywords: DNA damage, detection, electrochemiluminescence, sensor

Procedia PDF Downloads 411
1609 The Analysis of Brain Response to Auditory Stimuli through EEG Signals’ Non-Linear Analysis

Authors: H. Namazi, H. T. N. Kuan

Abstract:

Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to auditory stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to auditory stimuli but provide us with very good recommendations for clinical purposes.

Keywords: auditory stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

Procedia PDF Downloads 536
1608 Multi Objective Near-Optimal Trajectory Planning of Mobile Robot

Authors: Amar Khoukhi, Mohamed Shahab

Abstract:

This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

Procedia PDF Downloads 372
1607 A Study of Using Different Printed Circuit Board Design Methods on Ethernet Signals

Authors: Bahattin Kanal, Nursel Akçam

Abstract:

Data transmission size and frequency requirements are increasing rapidly in electronic communication protocols. Increasing data transmission speeds have made the design of printed circuit boards much more important. It is important to carefully examine the requirements and make analyses before and after the design of the digital electronic circuit board. It delves into impedance matching techniques, signal trace routing considerations, and the impact of layer stacking on signal performance. The paper extensively explores techniques for minimizing crosstalk issues and interference, presenting a holistic perspective on design strategies to optimize the quality of high-speed signals. Through a comprehensive review of these design methodologies, this study aims to provide insights into achieving reliable and high-performance printed circuit board layouts for these signals. In this study, the effect of different design methods on Ethernet signals was examined from the type of S parameters. Siemens company HyperLynx software tool was used for the analyses.

Keywords: HyperLynx, printed circuit board, s parameters, ethernet

Procedia PDF Downloads 41
1606 Coordination of Traffic Signals on Arterial Streets in Duhok City

Authors: Dilshad Ali Mohammed, Ziyad Nayef Shamsulddin Aldoski, Millet Salim Mohammed

Abstract:

The increase in levels of traffic congestion along urban signalized arterials needs efficient traffic management. The application of traffic signal coordination can improve the traffic operation and safety for a series of signalized intersection along the arterials. The objective of this study is to evaluate the benefits achievable through actuated traffic signal coordination and make a comparison in control delay against the same signalized intersection in case of being isolated. To accomplish this purpose, a series of eight signalized intersections located on two major arterials in Duhok City was chosen for conducting the study. Traffic data (traffic volumes, link and approach speeds, and passenger car equivalent) were collected at peak hours. Various methods had been used for collecting data such as video recording technique, moving vehicle method and manual methods. Geometric and signalization data were also collected for the purpose of the study. The coupling index had been calculated to check the coordination attainability, and then time space diagrams were constructed representing one-way coordination for the intersections on Barzani and Zakho Streets, and others represented two-way coordination for the intersections on Zakho Street with accepted progression bandwidth efficiency. The results of this study show great progression bandwidth of 54 seconds for east direction coordination and 17 seconds for west direction coordination on Barzani Street under suggested controlled speed of 60 kph agreeable with the present data. For Zakho Street, the progression bandwidth is 19 seconds for east direction coordination and 18 seconds for west direction coordination under suggested controlled speed of 40 kph. The results show that traffic signal coordination had led to high reduction in intersection control delays on both arterials.

Keywords: bandwidth, congestion, coordination, traffic, signals, streets

Procedia PDF Downloads 312
1605 Adaptive Motion Planning for 6-DOF Robots Based on Trigonometric Functions

Authors: Jincan Li, Mingyu Gao, Zhiwei He, Yuxiang Yang, Zhongfei Yu, Yuanyuan Liu

Abstract:

Building an appropriate motion model is crucial for trajectory planning of robots and determines the operational quality directly. An adaptive acceleration and deceleration motion planning based on trigonometric functions for the end-effector of 6-DOF robots in Cartesian coordinate system is proposed in this paper. This method not only achieves the smooth translation motion and rotation motion by constructing a continuous jerk model, but also automatically adjusts the parameters of trigonometric functions according to the variable inputs and the kinematic constraints. The results of computer simulation show that this method is correct and effective to achieve the adaptive motion planning for linear trajectories.

Keywords: kinematic constraints, motion planning, trigonometric function, 6-DOF robots

Procedia PDF Downloads 274
1604 Design of Labview Based DAQ System

Authors: Omar A. A. Shaebi, Matouk M. Elamari, Salaheddin Allid

Abstract:

The Information Computing System of Monitoring (ICSM) for the Research Reactor of Tajoura Nuclear Research Centre (TNRC) stopped working since early 1991. According to the regulations, the computer is necessary to operate the reactor up to its maximum power (10 MW). The fund is secured via IAEA to develop a modern computer based data acquisition system to replace the old computer. This paper presents the development of the Labview based data acquisition system to allow automated measurements using National Instruments Hardware and its labview software. The developed system consists of SCXI 1001 chassis, the chassis house four SCXI 1100 modules each can maintain 32 variables. The chassis is interfaced with the PC using NI PCI-6023 DAQ Card. Labview, developed by National Instruments, is used to run and operate the DAQ System. Labview is graphical programming environment suited for high level design. It allows integrating different signal processing components or subsystems within a graphical framework. The results showed system capabilities in monitoring variables, acquiring and saving data. Plus the capability of the labview to control the DAQ.

Keywords: data acquisition, labview, signal conditioning, national instruments

Procedia PDF Downloads 497
1603 Impact of Geomagnetic Storm on Ionosphere

Authors: Affan Ahmed

Abstract:

This research investigates the impact of the geomagnetic storm occurring from April 22 to April 26, 2023, on the Earth’s ionosphere, with a focus on analyzing specific ionospheric parameters to understand the storm's effects on ionospheric stability and GNSS signal propagation. Geomagnetic storms, caused by intensified solar wind-magnetosphere interactions, can significantly disturb ionospheric conditions, impacting electron density, Total Electron Content (TEC), and thermospheric composition. Such disturbances are particularly relevant to satellite-based navigation and communication systems, as fluctuations in ionospheric parameters can degrade signal integrity and reliability. In this study, data were obtained from multiple sources, including OMNIWeb for parameters like Dst, Kp, Bz, Electric Field, and solar wind pressure, GUVI for O/N₂ ratio maps, and TEC data from low-, mid-, and high-latitude stations available on the IONOLAB website. Additional Equatorial Electrojet (EEJ) and geomagnetic data were acquired from INTERMAGNET. The methodology involved comparing storm-affected data from April 22 to April 26 with quiet days in April 2023, using statistical and wavelet analysis to assess variations in parameters like TEC, O/N₂ ratio, and geomagnetic indices. The results show pronounced fluctuations in TEC and other ionospheric parameters during the main phase of the storm, with spatial variations observed across latitudes, highlighting the global response of the ionosphere to geomagnetic disturbances. The findings underline the storm’s significant impact on ionospheric composition, particularly in mid- and high-latitude regions, which correlates with increased GNSS signal interference in these areas. This study contributes to understanding the ionosphere’s response to geomagnetic activity, emphasizing the need for robust models to predict and mitigate space weather effects on GNSS-dependent technologies.

Keywords: geomagnetic storms, ionospheric disturbances, space weather effects, magnetosphere-ionosphere coupling

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1602 Strength Analysis of RCC Dams Subject to the Layer-by-Layer Construction Method

Authors: Archil Motsonelidze, Vitaly Dvalishvili

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Existing roller compacted concrete (RCC) dams indicate that the layer-by-layer construction method gives considerable economies as compared with the conventional methods. RCC dams have also gained acceptance in the regions of high seismic activity. Earthquake resistance analysis of RCC gravity dams based on nonlinear finite element technique is presented. An elastic-plastic approach is used to describe the material of a dam while it is under static conditions (period of construction). Seismic force, as an acceleration equivalent to that produced by a real earthquake, is supposed to act when the dam is completed. The materials of the dam and foundation may be nonhomogeneous and anisotropic. The “dam-foundation” system is idealized as a plain strain problem.

Keywords: finite element method, layer-by-layer construction, RCC dams, strength analysis

Procedia PDF Downloads 552
1601 Micromechanism of Ionization Effects on Metal/Gas Mixing Instabilty at Extreme Shock Compressing Conditions

Authors: Shenghong Huang, Weirong Wang, Xisheng Luo, Xinzhu Li, Xinwen Zhao

Abstract:

Understanding of material mixing induced by Richtmyer-Meshkov instability (RMI) at extreme shock compressing conditions (high energy density environment: P >> 100GPa, T >> 10000k) is of great significance in engineering and science, such as inertial confinement fusion(ICF), supersonic combustion, etc. Turbulent mixing induced by RMI is a kind of complex fluid dynamics, which is closely related with hydrodynamic conditions, thermodynamic states, material physical properties such as compressibility, strength, surface tension and viscosity, etc. as well as initial perturbation on interface. For phenomena in ordinary thermodynamic conditions (low energy density environment), many investigations have been conducted and many progresses have been reported, while for mixing in extreme thermodynamic conditions, the evolution may be very different due to ionization as well as large difference of material physical properties, which is full of scientific problems and academic interests. In this investigation, the first principle based molecular dynamic method is applied to study metal Lithium and gas Hydrogen (Li-H2) interface mixing in micro/meso scale regime at different shock compressing loading speed ranging from 3 km/s to 30 km/s. It's found that, 1) Different from low-speed shock compressing cases, in high-speed shock compresing (>9km/s) cases, a strong acceleration of metal/gas interface after strong shock compression is observed numerically, leading to a strong phase inverse and spike growing with a relative larger linear rate. And more specially, the spike growing rate is observed to be increased with shock loading speed, presenting large discrepancy with available empirical RMI models; 2) Ionization is happened in shock font zone at high-speed loading cases(>9km/s). An additional local electric field induced by the inhomogeneous diffusion of electrons and nuclei after shock font is observed to occur near the metal/gas interface, leading to a large acceleration of nuclei in this zone; 3) In conclusion, the work of additional electric field contributes to a mechanism of RMI in micro/meso scale regime at extreme shock compressing conditions, i.e., a Rayleigh-Taylor instability(RTI) is induced by additional electric field during RMI mixing process and thus a larger linear growing rate of interface spike.

Keywords: ionization, micro/meso scale, material mixing, shock

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1600 Stability Analysis and Controller Design of Further Development of Miniaturized Mössbauer Spectrometer II for Space Applications with Focus on the Extended Lyapunov Method – Part I –

Authors: Mohammad Beyki, Justus Pawlak, Robert Patzke, Franz Renz

Abstract:

In the context of planetary exploration, the MIMOS II (miniaturized Mössbauer spectrometer) serves as a proven and reliable measuring instrument. The transmission behaviour of the electronics in the Mössbauer spectroscopy is newly developed and optimized. For this purpose, the overall electronics is split into three parts. This elaboration deals exclusively with the first part of the signal chain for the evaluation of photons in experiments with gamma radiation. Parallel to the analysis of the electronics, a new method for the stability consideration of linear and non-linear systems is presented: The extended method of Lyapunov’s stability criteria. The design helps to weigh advantages and disadvantages against other simulated circuits in order to optimize the MIMOS II for the terestric and extraterestric measurment. Finally, after stability analysis, the controller design according to Ackermann is performed, achieving the best possible optimization of the output variable through a skillful pole assignment.

Keywords: Mössbauer spectroscopy, electronic signal amplifier, light processing technology, photocurrent, trans-impedance amplifier, extended Lyapunov method

Procedia PDF Downloads 103
1599 Brain Computer Interface Implementation for Affective Computing Sensing: Classifiers Comparison

Authors: Ramón Aparicio-García, Gustavo Juárez Gracia, Jesús Álvarez Cedillo

Abstract:

A research line of the computer science that involve the study of the Human-Computer Interaction (HCI), which search to recognize and interpret the user intent by the storage and the subsequent analysis of the electrical signals of the brain, for using them in the control of electronic devices. On the other hand, the affective computing research applies the human emotions in the HCI process helping to reduce the user frustration. This paper shows the results obtained during the hardware and software development of a Brain Computer Interface (BCI) capable of recognizing the human emotions through the association of the brain electrical activity patterns. The hardware involves the sensing stage and analogical-digital conversion. The interface software involves algorithms for pre-processing of the signal in time and frequency analysis and the classification of patterns associated with the electrical brain activity. The methods used for the analysis and classification of the signal have been tested separately, by using a database that is accessible to the public, besides to a comparison among classifiers in order to know the best performing.

Keywords: affective computing, interface, brain, intelligent interaction

Procedia PDF Downloads 393