Hydrogen is emerging as a promising alternative to fossil fuels in the transportation sector.This study evaluated the feasibility of estab-lishing hydrogen refueling stations in five cities in Oman,Duqm,Haima,Sur,Al B...Hydrogen is emerging as a promising alternative to fossil fuels in the transportation sector.This study evaluated the feasibility of estab-lishing hydrogen refueling stations in five cities in Oman,Duqm,Haima,Sur,Al Buraymi,and Salalah,using Hybrid Optimization of Multiple Electric Renewables(HOMER)software.Three hybrid energy systems,photovoltaic-wind turbine-battery,photovoltaic-battery,and wind turbine-battery were analyzed for each city.Results indicated that Duqm offers the lowest net present cost(NPC),levelized cost of energy,and levelized cost of hydrogen,making it the most cost-effective location.Additionally,Sensitivity analysis showed that as the life of electrolyzer increases during operation,the initial capital expenditure is distributed over a longer operational period,leading to a reduction in the NPC.More so,renewable energy systems produced no emissions which supports Oman’s mission target.This comprehensive analysis confirms the feasibility of establishing a hydrogen refueling station in Duqm,Oman,and highlights advanced optimization techniques’superior capability in designing cost-effective,sustainable energy systems.展开更多
A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this paper.With this control scheme,the performance against disturbances,uncertainties,and attenuation is...A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this paper.With this control scheme,the performance against disturbances,uncertainties,and attenuation is enhanced.Linear active disturbance rejection control(LADRC)is mainly based on an extended state observer(ESO)technology.A fractional integral(FOI)action is combined with the LADRC technique which proposes a hybrid control scheme like FO-LADRC.Incorporating this FOI action improves the robustness of the standard LADRC.The set-point tracking of the proposed FO-LADRC scheme is designed by Bode’s ideal transfer function(BITF)based robust closed-loop concept,an appropriate pole placement method.The effectiveness of the proposed FO-LADRC scheme is illustrated through experimental results on the linear flexible joint system(LFJS).The results show the enhancement of the robustness with disturbance rejection.Furthermore,a comparative analysis is presented with the results obtained using the integer-order LADRC and FO-LADRC scheme.展开更多
Speech recognition allows the machine to turn the speech signal into text through identification and understanding process. Extract the features, predict the maximum likelihood, and generate the models of the input sp...Speech recognition allows the machine to turn the speech signal into text through identification and understanding process. Extract the features, predict the maximum likelihood, and generate the models of the input speech signal are considered the most important steps to configure the Automatic Speech Recognition System (ASR). In this paper, an automatic Arabic speech recognition system was established using MATLAB and 24 Arabic words Consonant-Vowel Consonant-Vowel Consonant-Vowel (CVCVCV) was recorded from 19 Arabic native speakers, each speaker uttering the same word 3 times (total 1368 words). In order to test the system, 39-features were extracted by partitioning the speech signal into frames ~ 0.25 sec shifted by 0.10 sec. in back-end, the statistical models were generated by separated the features into number of states between 4 to 10, each state has 8-gaussian distributions. The data has 48 k sample rate and 32-bit depth and saved separately in a wave file format. The system was trained in phonetically rich and balanced Arabic speech words list (10 speakers * 3 times * 24 words, total 720 words) and tested using another word list (24 words * 9 speakers * 3 times *, total 648 words). Using different speakers similar words, the system obtained a very good word recognition accuracy results of 92.92% and a Word Error Rate (WER) of 7.08%.展开更多
In recent years, the accuracy of speech recognition (SR) has been one of the most active areas of research. Despite that SR systems are working reasonably well in quiet conditions, they still suffer severe performance...In recent years, the accuracy of speech recognition (SR) has been one of the most active areas of research. Despite that SR systems are working reasonably well in quiet conditions, they still suffer severe performance degradation in noisy conditions or distorted channels. It is necessary to search for more robust feature extraction methods to gain better performance in adverse conditions. This paper investigates the performance of conventional and new hybrid speech feature extraction algorithms of Mel Frequency Cepstrum Coefficient (MFCC), Linear Prediction Coding Coefficient (LPCC), perceptual linear production (PLP), and RASTA-PLP in noisy conditions through using multivariate Hidden Markov Model (HMM) classifier. The behavior of the proposal system is evaluated using TIDIGIT human voice dataset corpora, recorded from 208 different adult speakers in both training and testing process. The theoretical basis for speech processing and classifier procedures were presented, and the recognition results were obtained based on word recognition rate.展开更多
The year of 2019 is the first deployment year of the fifth generation(5G)mobile communications.As we are writing the editorial for this special issue,a list of countries such as South Korea,the United States,China,Swi...The year of 2019 is the first deployment year of the fifth generation(5G)mobile communications.As we are writing the editorial for this special issue,a list of countries such as South Korea,the United States,China,Switzerland,the United Kingdom,and Spain have launched commercial 5G services for the general public,while this list is growing quickly and is envisioned to become much longer in the near future.For the past months,5G has been continuously a hot buzzword in the news,attracting a huge focus from the whole society.展开更多
Wake-Up-Word Speech Recognition task (WUW-SR) is a computationally very demand, particularly the stage of feature extraction which is decoded with corresponding Hidden Markov Models (HMMs) in the back-end stage of the...Wake-Up-Word Speech Recognition task (WUW-SR) is a computationally very demand, particularly the stage of feature extraction which is decoded with corresponding Hidden Markov Models (HMMs) in the back-end stage of the WUW-SR. The state of the art WUW-SR system is based on three different sets of features: Mel-Frequency Cepstral Coefficients (MFCC), Linear Predictive Coding Coefficients (LPC), and Enhanced Mel-Frequency Cepstral Coefficients (ENH_MFCC). In (front-end of Wake-Up-Word Speech Recognition System Design on FPGA) [1], we presented an experimental FPGA design and implementation of a novel architecture of a real-time spectrogram extraction processor that generates MFCC, LPC, and ENH_MFCC spectrograms simultaneously. In this paper, the details of converting the three sets of spectrograms 1) Mel-Frequency Cepstral Coefficients (MFCC), 2) Linear Predictive Coding Coefficients (LPC), and 3) Enhanced Mel-Frequency Cepstral Coefficients (ENH_MFCC) to their equivalent features are presented. In the WUW- SR system, the recognizer’s frontend is located at the terminal which is typically connected over a data network to remote back-end recognition (e.g., server). The WUW-SR is shown in Figure 1. The three sets of speech features are extracted at the front-end. These extracted features are then compressed and transmitted to the server via a dedicated channel, where subsequently they are decoded.展开更多
Photovoltaic(PV)modules age with time for various reasons such as corroded joints and terminals and glass coating defects,and their ageing degrades the PV array power.With the help of the PV array numerical model,this...Photovoltaic(PV)modules age with time for various reasons such as corroded joints and terminals and glass coating defects,and their ageing degrades the PV array power.With the help of the PV array numerical model,this paper explores the effects of PV module ageing on the PV array power,and the power gains and costs of rearranging and recabling aged PV modules in a PV array.The numerical PV array model is first revised to account for module ageing,rearrangement and recabling,with the relevant equations presented herein.The updated numerical model is then used to obtain the array powers for seven different PV arrays.The power results are then analysed in view of the attributes of the seven PV array examples.A guiding method to recommend recabling after rearranging aged modules is then proposed,leading to further significant power gains,while eliminating intra-row mismatches.When certain conditions are met,it was shown that recabling PV modules after rearranging them may lead to further significant power gains,reaching 57%and 98%in two considered PV array examples.Higher gains are possible in other arrays.A cost-benefit analysis weighing annual power gains versus estimated recabling costs is also given for the seven considered PV array examples to guide recabling decisions based on technical and economic merits.In the considered examples,recabling costs can be recovered in<4 years.Compared with the powers of the aged arrays,power gains due to our proposed rearranging and recabling the PV arrays ranged between 73%and 131%in the considered examples—well over the gains reported in the literature.Moreover,the cost of our static module rearrangement and recabling method outshines the costs of dynamic reconfiguration methods recently published in the literature.展开更多
Nonlinear encoding of optical information can be achieved using various forms of data representation.Here,we analyze the performances of different nonlinear information encoding strategies that can be employed in diff...Nonlinear encoding of optical information can be achieved using various forms of data representation.Here,we analyze the performances of different nonlinear information encoding strategies that can be employed in diffractive optical processors based on linear materials and shed light on their utility and performance gaps compared to the state-of-the-art digital deep neural networks.For a comprehensive evaluation,we used different datasets to compare the statistical inference performance of simpler-to-implement nonlinear encoding strategies that involve,e.g.,phase encoding,against data repetition-based nonlinear encoding strategies.We show that data repetition within a diffractive volume(e.g.,through an optical cavity or cascaded introduction of the input data)causes the loss of the universal linear transformation capability of a diffractive optical processor.Therefore,data repetition-based diffractive blocks cannot provide optical analogs to fully connected or convolutional layers commonly employed in digital neural networks.However,they can still be effectively trained for specific inference tasks and achieve enhanced accuracy,benefiting from the nonlinear encoding of the input information.Our results also reveal that phase encoding of input information without data repetition provides a simpler nonlinear encoding strategy with comparable statistical inference accuracy to data repetition-based diffractive processors.Our analyses and conclusions would be of broad interest to explore the push-pull relationship between linear material-based diffractive optical systems and nonlinear encoding strategies in visual information processors.展开更多
This study addresses the problem of deploying a group of mobile robots over a nonconvex region with obstacles.Assuming that the robots are equipped with omnidirectional range sensors of common radius,disjoint subsets ...This study addresses the problem of deploying a group of mobile robots over a nonconvex region with obstacles.Assuming that the robots are equipped with omnidirectional range sensors of common radius,disjoint subsets of the sensed area are assigned to the robots.These proximity-based subsets are calculated using the visibility notion,where the cell of each robot is treated as an opaque obstacle for the other robots.Based on that,optimal spatially distributed coordination algorithms are derived for the area coverage problem and for the homing problem,where the swarm needs to move to specific locations.Experimental studies demonstrate the results.展开更多
This study addresses the problem of efficiently navigating a differential drive mobile robot to a target pose in a region with obstacles,without explicitly generating a trajectory.The robot is assumed to be equipped w...This study addresses the problem of efficiently navigating a differential drive mobile robot to a target pose in a region with obstacles,without explicitly generating a trajectory.The robot is assumed to be equipped with an omnidirectional range sensor,while the region may or may not be a priori known.Given the known obstacles in each iteration of the controller,the shortest path connecting the robot and the target point provides a raw desired movement direction.Considering the unobstructed area in that direction,the size of the robot and the obstacle contours in its visibility range,the reference direction is determined.Finally,respecting the velocity and acceleration constraints of the robot,the angular velocity is properly selected to rotate the robot towards the reference direction,while the linear velocity is chosen to efficiently minimise the distance to the final target,as well as to avoid collisions.After the robot has reached the target,the controller switches to orientation mode in order to fix the orientation.Experimental studies demonstrate the effectiveness of the algorithm.展开更多
文摘Hydrogen is emerging as a promising alternative to fossil fuels in the transportation sector.This study evaluated the feasibility of estab-lishing hydrogen refueling stations in five cities in Oman,Duqm,Haima,Sur,Al Buraymi,and Salalah,using Hybrid Optimization of Multiple Electric Renewables(HOMER)software.Three hybrid energy systems,photovoltaic-wind turbine-battery,photovoltaic-battery,and wind turbine-battery were analyzed for each city.Results indicated that Duqm offers the lowest net present cost(NPC),levelized cost of energy,and levelized cost of hydrogen,making it the most cost-effective location.Additionally,Sensitivity analysis showed that as the life of electrolyzer increases during operation,the initial capital expenditure is distributed over a longer operational period,leading to a reduction in the NPC.More so,renewable energy systems produced no emissions which supports Oman’s mission target.This comprehensive analysis confirms the feasibility of establishing a hydrogen refueling station in Duqm,Oman,and highlights advanced optimization techniques’superior capability in designing cost-effective,sustainable energy systems.
基金This research work was funded by Institutional Fund Projects under Grant No.(IFPRC-027-135-2020).
文摘A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this paper.With this control scheme,the performance against disturbances,uncertainties,and attenuation is enhanced.Linear active disturbance rejection control(LADRC)is mainly based on an extended state observer(ESO)technology.A fractional integral(FOI)action is combined with the LADRC technique which proposes a hybrid control scheme like FO-LADRC.Incorporating this FOI action improves the robustness of the standard LADRC.The set-point tracking of the proposed FO-LADRC scheme is designed by Bode’s ideal transfer function(BITF)based robust closed-loop concept,an appropriate pole placement method.The effectiveness of the proposed FO-LADRC scheme is illustrated through experimental results on the linear flexible joint system(LFJS).The results show the enhancement of the robustness with disturbance rejection.Furthermore,a comparative analysis is presented with the results obtained using the integer-order LADRC and FO-LADRC scheme.
文摘Speech recognition allows the machine to turn the speech signal into text through identification and understanding process. Extract the features, predict the maximum likelihood, and generate the models of the input speech signal are considered the most important steps to configure the Automatic Speech Recognition System (ASR). In this paper, an automatic Arabic speech recognition system was established using MATLAB and 24 Arabic words Consonant-Vowel Consonant-Vowel Consonant-Vowel (CVCVCV) was recorded from 19 Arabic native speakers, each speaker uttering the same word 3 times (total 1368 words). In order to test the system, 39-features were extracted by partitioning the speech signal into frames ~ 0.25 sec shifted by 0.10 sec. in back-end, the statistical models were generated by separated the features into number of states between 4 to 10, each state has 8-gaussian distributions. The data has 48 k sample rate and 32-bit depth and saved separately in a wave file format. The system was trained in phonetically rich and balanced Arabic speech words list (10 speakers * 3 times * 24 words, total 720 words) and tested using another word list (24 words * 9 speakers * 3 times *, total 648 words). Using different speakers similar words, the system obtained a very good word recognition accuracy results of 92.92% and a Word Error Rate (WER) of 7.08%.
文摘In recent years, the accuracy of speech recognition (SR) has been one of the most active areas of research. Despite that SR systems are working reasonably well in quiet conditions, they still suffer severe performance degradation in noisy conditions or distorted channels. It is necessary to search for more robust feature extraction methods to gain better performance in adverse conditions. This paper investigates the performance of conventional and new hybrid speech feature extraction algorithms of Mel Frequency Cepstrum Coefficient (MFCC), Linear Prediction Coding Coefficient (LPCC), perceptual linear production (PLP), and RASTA-PLP in noisy conditions through using multivariate Hidden Markov Model (HMM) classifier. The behavior of the proposal system is evaluated using TIDIGIT human voice dataset corpora, recorded from 208 different adult speakers in both training and testing process. The theoretical basis for speech processing and classifier procedures were presented, and the recognition results were obtained based on word recognition rate.
文摘The year of 2019 is the first deployment year of the fifth generation(5G)mobile communications.As we are writing the editorial for this special issue,a list of countries such as South Korea,the United States,China,Switzerland,the United Kingdom,and Spain have launched commercial 5G services for the general public,while this list is growing quickly and is envisioned to become much longer in the near future.For the past months,5G has been continuously a hot buzzword in the news,attracting a huge focus from the whole society.
文摘Wake-Up-Word Speech Recognition task (WUW-SR) is a computationally very demand, particularly the stage of feature extraction which is decoded with corresponding Hidden Markov Models (HMMs) in the back-end stage of the WUW-SR. The state of the art WUW-SR system is based on three different sets of features: Mel-Frequency Cepstral Coefficients (MFCC), Linear Predictive Coding Coefficients (LPC), and Enhanced Mel-Frequency Cepstral Coefficients (ENH_MFCC). In (front-end of Wake-Up-Word Speech Recognition System Design on FPGA) [1], we presented an experimental FPGA design and implementation of a novel architecture of a real-time spectrogram extraction processor that generates MFCC, LPC, and ENH_MFCC spectrograms simultaneously. In this paper, the details of converting the three sets of spectrograms 1) Mel-Frequency Cepstral Coefficients (MFCC), 2) Linear Predictive Coding Coefficients (LPC), and 3) Enhanced Mel-Frequency Cepstral Coefficients (ENH_MFCC) to their equivalent features are presented. In the WUW- SR system, the recognizer’s frontend is located at the terminal which is typically connected over a data network to remote back-end recognition (e.g., server). The WUW-SR is shown in Figure 1. The three sets of speech features are extracted at the front-end. These extracted features are then compressed and transmitted to the server via a dedicated channel, where subsequently they are decoded.
文摘Photovoltaic(PV)modules age with time for various reasons such as corroded joints and terminals and glass coating defects,and their ageing degrades the PV array power.With the help of the PV array numerical model,this paper explores the effects of PV module ageing on the PV array power,and the power gains and costs of rearranging and recabling aged PV modules in a PV array.The numerical PV array model is first revised to account for module ageing,rearrangement and recabling,with the relevant equations presented herein.The updated numerical model is then used to obtain the array powers for seven different PV arrays.The power results are then analysed in view of the attributes of the seven PV array examples.A guiding method to recommend recabling after rearranging aged modules is then proposed,leading to further significant power gains,while eliminating intra-row mismatches.When certain conditions are met,it was shown that recabling PV modules after rearranging them may lead to further significant power gains,reaching 57%and 98%in two considered PV array examples.Higher gains are possible in other arrays.A cost-benefit analysis weighing annual power gains versus estimated recabling costs is also given for the seven considered PV array examples to guide recabling decisions based on technical and economic merits.In the considered examples,recabling costs can be recovered in<4 years.Compared with the powers of the aged arrays,power gains due to our proposed rearranging and recabling the PV arrays ranged between 73%and 131%in the considered examples—well over the gains reported in the literature.Moreover,the cost of our static module rearrangement and recabling method outshines the costs of dynamic reconfiguration methods recently published in the literature.
基金supported by the U.S.Department of Energy(DOE),Office of Basic Energy Sciences,Division of Materials Sciences and Engineering under Award#DE-SC0023088.
文摘Nonlinear encoding of optical information can be achieved using various forms of data representation.Here,we analyze the performances of different nonlinear information encoding strategies that can be employed in diffractive optical processors based on linear materials and shed light on their utility and performance gaps compared to the state-of-the-art digital deep neural networks.For a comprehensive evaluation,we used different datasets to compare the statistical inference performance of simpler-to-implement nonlinear encoding strategies that involve,e.g.,phase encoding,against data repetition-based nonlinear encoding strategies.We show that data repetition within a diffractive volume(e.g.,through an optical cavity or cascaded introduction of the input data)causes the loss of the universal linear transformation capability of a diffractive optical processor.Therefore,data repetition-based diffractive blocks cannot provide optical analogs to fully connected or convolutional layers commonly employed in digital neural networks.However,they can still be effectively trained for specific inference tasks and achieve enhanced accuracy,benefiting from the nonlinear encoding of the input information.Our results also reveal that phase encoding of input information without data repetition provides a simpler nonlinear encoding strategy with comparable statistical inference accuracy to data repetition-based diffractive processors.Our analyses and conclusions would be of broad interest to explore the push-pull relationship between linear material-based diffractive optical systems and nonlinear encoding strategies in visual information processors.
文摘This study addresses the problem of deploying a group of mobile robots over a nonconvex region with obstacles.Assuming that the robots are equipped with omnidirectional range sensors of common radius,disjoint subsets of the sensed area are assigned to the robots.These proximity-based subsets are calculated using the visibility notion,where the cell of each robot is treated as an opaque obstacle for the other robots.Based on that,optimal spatially distributed coordination algorithms are derived for the area coverage problem and for the homing problem,where the swarm needs to move to specific locations.Experimental studies demonstrate the results.
文摘This study addresses the problem of efficiently navigating a differential drive mobile robot to a target pose in a region with obstacles,without explicitly generating a trajectory.The robot is assumed to be equipped with an omnidirectional range sensor,while the region may or may not be a priori known.Given the known obstacles in each iteration of the controller,the shortest path connecting the robot and the target point provides a raw desired movement direction.Considering the unobstructed area in that direction,the size of the robot and the obstacle contours in its visibility range,the reference direction is determined.Finally,respecting the velocity and acceleration constraints of the robot,the angular velocity is properly selected to rotate the robot towards the reference direction,while the linear velocity is chosen to efficiently minimise the distance to the final target,as well as to avoid collisions.After the robot has reached the target,the controller switches to orientation mode in order to fix the orientation.Experimental studies demonstrate the effectiveness of the algorithm.
