The global financial and economic market is now made up of several structures that are powerful and complex.In the last few decades,a few techniques and theories have been implemented that have revolutionized the unde...The global financial and economic market is now made up of several structures that are powerful and complex.In the last few decades,a few techniques and theories have been implemented that have revolutionized the understanding of those systems to forecast financial markets based on time series analysis.However still,none has been shown to function successfully consistently.In this project,a special form of Neural Network Modeling called LSTM to forecast the foreign exchange rate of currencies.In several different forecasting applications,this method of modelling has become popular as it can be defined complex non-linear relationships between variables and the outcome it wishes to predict.In compare to the stock market,exchange rates tend to be more relevant due to the availability of macroeconomic data that can be used to train the network to learn the impact of particular variables on the rate to be predicted.The information was collected using Quandl,an economic and financial platform that offers quantitative indicators for a wide variety of countries.Model is compared with three different metrics by exponential moving average and an autoregressive integrated moving average.then compare and validate the ability of the model to reliably predict future values and compare which of the models predicted the most correctly.展开更多
Parkinson’s Disease(PD)is a neurodegenerative disease which shows a deficiency in dopaminehormone in the brain.It is a common irreversible impairment among elderly people.Identifying this disease in its preliminary s...Parkinson’s Disease(PD)is a neurodegenerative disease which shows a deficiency in dopaminehormone in the brain.It is a common irreversible impairment among elderly people.Identifying this disease in its preliminary stage is important to improve the efficacy of the treatment process.Disordered gait is one of the key indications of early symptoms of PD.Therefore,the present paper introduces a novel approach to identify pa rkinsonian gait using raw vertical spatiotemporal ground reaction force.A convolution neural network(CNN)is implemented to identify the features in the parkinsonian gaits and their progressive stages.Moreover,the var iations of the gait pressures were visually recreated using ANSYS finite element software package.The CNN model has shown a 97%accuracy of recognizing parkinsonian gait and their different stages,and ANSYS model is implemented to visualize the pressure variation of the foot during a bottom-up approach.展开更多
Cymatics is a visual representation of sound and vibrations,on surfaces of plates,diaphragms,and membranes in the forms of auditory-images.The surfaces that are exposed to these vibrations are sprinkled with fine part...Cymatics is a visual representation of sound and vibrations,on surfaces of plates,diaphragms,and membranes in the forms of auditory-images.The surfaces that are exposed to these vibrations are sprinkled with fine particles that accumulate at nodes,to create visualizations of specific geometry unique to the particular frequency.This paper discusses the designing of an experimental platform,dedicated towards observing the behavior of cymatics,through analysis of such visualizations(Chladni patterns).This is further investigated by performing a numerical modelling using finite element simulation.Two millimeter thickness Aluminum(Al)plates of three shapes consisting of surfaces with equal areas were used for both experimental and finite element analysis(FEA).FEA was performed using ANSYS simulation software and patterns were derived for different vibrational frequencies.The results demonstrated that the 60%of the experimental imagery conforms with the visualization generated by ANSYS software.Additionally,the lowest average frequency differences with respect to the simulation results an average deviation for similar images was found to be 9.2%and 2.8 mm for the triangular shape plate,validating that the shape of the plate plays a paramount role in cymatics analysis.An image processing technique was used to determine the deviation between the images created by experimental platform and FEA for all the three shapes.The results demonstrate that Chladni patterns are best represented by a triangular shaped plate.展开更多
Three wheelers(3 Ws)are widely used in low and middle-income countries,particularly in Asia Pacific region as a comparatively cheap method to passenger transportation and goods delivery.The frequent use of 3 Ws in day...Three wheelers(3 Ws)are widely used in low and middle-income countries,particularly in Asia Pacific region as a comparatively cheap method to passenger transportation and goods delivery.The frequent use of 3 Ws in day-to-day activities have caused a large number of accidents causing injuries to their passengers.Less research has been carried out to identify the reasons behind 3 W accidents.The survey carried out prior to this research has identified that the stability control and speed control are the two key factors which the 3 W accidents attributed to.3 W fork is the main mechanical element that controls the balance and the stability of the vehicle.A damaged 3 W fork(a physical damage or a slight deformation)unbalances the 3 W and had been identified as one of the reasons for large number of accidents.Therefore,correctly reforming the damaged fork is of paramount importance,when concerning the safety of the 3 Ws.Traditionally,both heat-treating and cold-working techniques are used in the mending processes.Not only this manual-labor repairing process weakens the strength of the fork,but also the profile produced is inaccurate.This paper discusses a hydraulic operated fork mending machine with an image processing technique to reform the damaged forks in 3 Ws.An image comparator-based imaging technique is used for this machine vision-based visually guided fork repairing process.Three cameras have been used to capture the images from three perpendicular directions.A contour sketch of the original fork(before the deformation occurs)has been compared against the faulty fork,to assist the worker to carry out the repairing process.The preliminary experimentations have shown that the proposed technique can improve the repositioning of the camber angle by repairing the damaged fork.展开更多
Leg amputations are common in accidents and diseases.The present active bionic legs use Electromyography(EMG)signals in lower limbs(just before the location of the amputation)to generate active control signals.The act...Leg amputations are common in accidents and diseases.The present active bionic legs use Electromyography(EMG)signals in lower limbs(just before the location of the amputation)to generate active control signals.The active control with EMGs greatly limits the potential of using these bionic legs because most accidents and diseases cause severe damages to tissues/muscles which originates EMG signals.As an alternative,the present research attempted to use an upper limb swing pattern to control an active bionic leg.A deep neural network(DNN)model is implemented to recognize the patterns in upper limb swing,and it is used to translate these signals into active control input of a bionic leg.The proposed approach can generate a full gait cycle within 1082 milliseconds,and it is comparable to the normal(a person without any disability)1070 milliseconds gait cycle.展开更多
文摘The global financial and economic market is now made up of several structures that are powerful and complex.In the last few decades,a few techniques and theories have been implemented that have revolutionized the understanding of those systems to forecast financial markets based on time series analysis.However still,none has been shown to function successfully consistently.In this project,a special form of Neural Network Modeling called LSTM to forecast the foreign exchange rate of currencies.In several different forecasting applications,this method of modelling has become popular as it can be defined complex non-linear relationships between variables and the outcome it wishes to predict.In compare to the stock market,exchange rates tend to be more relevant due to the availability of macroeconomic data that can be used to train the network to learn the impact of particular variables on the rate to be predicted.The information was collected using Quandl,an economic and financial platform that offers quantitative indicators for a wide variety of countries.Model is compared with three different metrics by exponential moving average and an autoregressive integrated moving average.then compare and validate the ability of the model to reliably predict future values and compare which of the models predicted the most correctly.
文摘Parkinson’s Disease(PD)is a neurodegenerative disease which shows a deficiency in dopaminehormone in the brain.It is a common irreversible impairment among elderly people.Identifying this disease in its preliminary stage is important to improve the efficacy of the treatment process.Disordered gait is one of the key indications of early symptoms of PD.Therefore,the present paper introduces a novel approach to identify pa rkinsonian gait using raw vertical spatiotemporal ground reaction force.A convolution neural network(CNN)is implemented to identify the features in the parkinsonian gaits and their progressive stages.Moreover,the var iations of the gait pressures were visually recreated using ANSYS finite element software package.The CNN model has shown a 97%accuracy of recognizing parkinsonian gait and their different stages,and ANSYS model is implemented to visualize the pressure variation of the foot during a bottom-up approach.
文摘Cymatics is a visual representation of sound and vibrations,on surfaces of plates,diaphragms,and membranes in the forms of auditory-images.The surfaces that are exposed to these vibrations are sprinkled with fine particles that accumulate at nodes,to create visualizations of specific geometry unique to the particular frequency.This paper discusses the designing of an experimental platform,dedicated towards observing the behavior of cymatics,through analysis of such visualizations(Chladni patterns).This is further investigated by performing a numerical modelling using finite element simulation.Two millimeter thickness Aluminum(Al)plates of three shapes consisting of surfaces with equal areas were used for both experimental and finite element analysis(FEA).FEA was performed using ANSYS simulation software and patterns were derived for different vibrational frequencies.The results demonstrated that the 60%of the experimental imagery conforms with the visualization generated by ANSYS software.Additionally,the lowest average frequency differences with respect to the simulation results an average deviation for similar images was found to be 9.2%and 2.8 mm for the triangular shape plate,validating that the shape of the plate plays a paramount role in cymatics analysis.An image processing technique was used to determine the deviation between the images created by experimental platform and FEA for all the three shapes.The results demonstrate that Chladni patterns are best represented by a triangular shaped plate.
文摘Three wheelers(3 Ws)are widely used in low and middle-income countries,particularly in Asia Pacific region as a comparatively cheap method to passenger transportation and goods delivery.The frequent use of 3 Ws in day-to-day activities have caused a large number of accidents causing injuries to their passengers.Less research has been carried out to identify the reasons behind 3 W accidents.The survey carried out prior to this research has identified that the stability control and speed control are the two key factors which the 3 W accidents attributed to.3 W fork is the main mechanical element that controls the balance and the stability of the vehicle.A damaged 3 W fork(a physical damage or a slight deformation)unbalances the 3 W and had been identified as one of the reasons for large number of accidents.Therefore,correctly reforming the damaged fork is of paramount importance,when concerning the safety of the 3 Ws.Traditionally,both heat-treating and cold-working techniques are used in the mending processes.Not only this manual-labor repairing process weakens the strength of the fork,but also the profile produced is inaccurate.This paper discusses a hydraulic operated fork mending machine with an image processing technique to reform the damaged forks in 3 Ws.An image comparator-based imaging technique is used for this machine vision-based visually guided fork repairing process.Three cameras have been used to capture the images from three perpendicular directions.A contour sketch of the original fork(before the deformation occurs)has been compared against the faulty fork,to assist the worker to carry out the repairing process.The preliminary experimentations have shown that the proposed technique can improve the repositioning of the camber angle by repairing the damaged fork.
文摘Leg amputations are common in accidents and diseases.The present active bionic legs use Electromyography(EMG)signals in lower limbs(just before the location of the amputation)to generate active control signals.The active control with EMGs greatly limits the potential of using these bionic legs because most accidents and diseases cause severe damages to tissues/muscles which originates EMG signals.As an alternative,the present research attempted to use an upper limb swing pattern to control an active bionic leg.A deep neural network(DNN)model is implemented to recognize the patterns in upper limb swing,and it is used to translate these signals into active control input of a bionic leg.The proposed approach can generate a full gait cycle within 1082 milliseconds,and it is comparable to the normal(a person without any disability)1070 milliseconds gait cycle.
