Hypergraphs can accurately capture complex higher-order relationships,but it is challenging to identify their important nodes.In this paper,an improved PageRank(ImPageRank)algorithm is designed to identify important n...Hypergraphs can accurately capture complex higher-order relationships,but it is challenging to identify their important nodes.In this paper,an improved PageRank(ImPageRank)algorithm is designed to identify important nodes in a directed hypergraph.The algorithm introduces the Jaccard similarity of directed hypergraphs.By comparing the numbers of common neighbors between nodes with the total number of their neighbors,the Jaccard similarity measure takes into account the similarity between nodes that are not directly connected,and can reflect the potential correlation between nodes.An improved susceptible–infected(SI)model in directed hypergraph is proposed,which considers nonlinear propagation mode and more realistic propagation mechanism.In addition,some important node evaluation methods are transferred from undirected hypergraphs and applied to directed hypergraphs.Finally,the ImPageRank algorithm is used to evaluate the performance of the SI model,network robustness and monotonicity.Simulations of real networks demonstrate the excellent performance of the proposed algorithm and provide a powerful framework for identifying important nodes in directed hypergraphs.展开更多
In this paper, we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model. We address the probl...In this paper, we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model. We address the problem of textures where neither the gray-level information nor the boundary information is adequate for object extraction. This is often the case of natural images composed of both homogeneous and textured regions. Because these images cannot be in general directly processed by the gray-level information, we propose a new texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry. Then, we use the popular Kullback-Leibler distance to design an active contour model which distinguishes the background and textures of interest. The existence of a minimizing solution to the proposed segmentation model is proven. Finally, a texture segmentation algorithm based on the Split-Bregrnan method is introduced to extract meaningful objects in a fast way. Promising synthetic and real-world results for gray-scale and color images are presented.展开更多
Viterbi decoding is widely used in many radio systems. Because of the large computation complexity, it is usually implemented with ASIC chips, FPGA chips, or optimized hardware accelerators. With the rapid development...Viterbi decoding is widely used in many radio systems. Because of the large computation complexity, it is usually implemented with ASIC chips, FPGA chips, or optimized hardware accelerators. With the rapid development of the multicore technology, multicore platforms become a reasonable choice for software radio (SR) systems. The Cell Broadband Engine processor is a state-of-art multi-core processor designed by Sony, Toshiba, and IBM. In this paper, we present a 64-state soft input Viterbi decoder for WiMAX SR Baseband system based on the Cell processor. With one Synergistic Processor Element (SPE) of a Cell Processor running at 3.2GHz, our Viterbi decoder can achieve the throughput up to 30Mb/s to decode the tail-biting convolutional code. The performance demonstrates that the proposed Viterbi decoding implementation is very efficient. Moreover, the Viterbi decoder can be easily integrated to the SR system and can provide a highly integrated SR solution. The optimization methodology in this module design can be extended to other modules on Cell platform.展开更多
Many studies suggest that EEG signals provide enough information for the detection of human emotions with feature based classification methods. However, very few studies have reported a classification method that reli...Many studies suggest that EEG signals provide enough information for the detection of human emotions with feature based classification methods. However, very few studies have reported a classification method that reliably works for individual participants (classification accuracy well over 90%). Further, a necessary condition for real life applications is a method that allows, irrespective of the immense individual difference among participants, to have minimal variance over the individual classification accuracy. We conducted offline computer aided emotion classification experiments using strict experimental controls. We analyzed EEG data collected from nine participants using validated film clips to induce four different emotional states (amused, disgusted, sad and neutral). The classification rate was evaluated using both unsupervised and supervised learning algorithms (in total seven “state of the art” algorithms were tested). The largest classification accuracy was computed by means of Support Vector Machine. Accuracy rate was on average 97.2%. The experimental protocol effectiveness was further supported by very small variance among individual participants’ classification accuracy (within interval: 96.7%, 98.3%). Classification accuracy evaluated on reduced number of electrodes suggested, consistently with psychological constructionist approaches, that we were able to classify emotions considering cortical activity from areas involved in emotion representation. The experimental protocol therefore appeared to be a key factor to improve the classification outcome by means of data quality improvements.展开更多
Generalized cross-correlation is considered as the most straightforward time delay estimation algorithm.Depending on various weighting function,different methods were derived and a straightforward method,named phase t...Generalized cross-correlation is considered as the most straightforward time delay estimation algorithm.Depending on various weighting function,different methods were derived and a straightforward method,named phase transform(PHAT)has been widely used.PHAT is well-known for its robustness to reverberation and its sensitivity to noise,which is partly due to the fact that PHAT distributes same weights to the frequencies dominated by signal or noise.To alleviate this problem,two weighting functions are proposed in this paper.By taking a posteriori signal-to-noise ratio(SNR)into account to classify reliable and unreliable frequencies,different weights could be assigned.The first proposed weighting function borrows the idea of binary mask and distributes same weights to frequencies in same set,whereas,the second one assigns weights based on coherence function.Experiments showed the robustness of proposed methods to reverberation and noise for improving the performance of time delay estimation through various criteria.展开更多
There are two key issues in distributed intrusion detection system,that is,maintaining load balance of system and protecting data integrity.To address these issues,this paper proposes a new distributed intrusion detec...There are two key issues in distributed intrusion detection system,that is,maintaining load balance of system and protecting data integrity.To address these issues,this paper proposes a new distributed intrusion detection model for big data based on nondestructive partitioning and balanced allocation.A data allocation strategy based on capacity and workload is introduced to achieve local load balance,and a dynamic load adjustment strategy is adopted to maintain global load balance of cluster.Moreover,data integrity is protected by using session reassemble and session partitioning.The simulation results show that the new model enjoys favorable advantages such as good load balance,higher detection rate and detection efficiency.展开更多
In order to assist physically handicapped persons in their movements,we developed an embedded isolated word speech recognition system(ASR)applied to voice control of smart wheelchairs.However,in spite of the existence...In order to assist physically handicapped persons in their movements,we developed an embedded isolated word speech recognition system(ASR)applied to voice control of smart wheelchairs.However,in spite of the existence in the industrial market of several kinds of electric wheelchairs,the problem remains the need to manually control this device by hand via joystick;which limits their use especially by people with severe disabilities.Thus,a significant number of disabled people cannot use a standard electric wheelchair or drive it with difficulty.The proposed solution is to use the voice to control and drive the wheelchair instead of classical joysticks.The intelligent chair is equipped with an obstacle detection system consisting of ultrasonic sensors,a moving navigation algorithm and a speech acquisition and recognition module for voice control embedded in a DSP card.The ASR architecture consists of two main modules.The first one is the speech parameterization module(features extraction)and the second module is the classifier which identifies the speech and generates the control word to motors power unit.The training and recognition phases are based on Hidden Markov Models(HMM),K-means,Baum-Welch and Viterbi algorithms.The database consists of 39 isolated speaker words(13 words pronounced 3 times under different environments and conditions).The simulations are tested under Matlab environment and the real-time implementation is performed by C language with code composer studio embedded in a TMS 320 C6416 DSP kit.The results and experiments obtained gave promising recognition ratio and accuracy around 99%in clean environment.However,the system accuracy decreases considerably in noisy environments,especially for SNR values below 5 dB(in street:78%,in factory:52%).展开更多
Image classification always has open challenges for computer vision research.Nowadays,deep learning has promoted the development of this field,especially in Convolutional Neural Networks(CNNs).This article proposes th...Image classification always has open challenges for computer vision research.Nowadays,deep learning has promoted the development of this field,especially in Convolutional Neural Networks(CNNs).This article proposes the development of efficiently scaled dilation of DropBlock optimization in CNNs for the fungus classification,which there are five species in this experiment.The proposed technique adjusts the convolution size at 35,45,and 60 with the max-polling size 2×2.The CNNs models are also designed in 12 models with the different BlockSizes and KeepProp.The proposed techniques provide maximum accuracy of 98.30%for the training set.Moreover,three accurate models,called Precision,Recall,and F1-score,are employed to measure the testing set.The experiment results expose that the proposed models achieve to classify the fungus and provide an excellent accuracy compared with the previous techniques.Furthermore,the proposed techniques can reduce the CNNs structure layer,directly affecting resource and time computation.展开更多
Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of...Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of the problem, a soft decision is often used as an optimal technique for speech restoration. In this paper, considering a new fashion of speech and noise models, we present two model-based soft decision techniques. One technique estimates a ratio mask generated by the exact Bayesian estimators of speech and noise. For the second technique, we consider one issue that an optimum local criterion(LC) for a certain SNR may not be appropriate for other SNRs. So we estimate a probabilistic mask with a variable LC. Experimental results show that the proposed method achieves a better performance than reference methods in speech quality.展开更多
Sound indexing and segmentation of digital documentsespecially in the internet and digital libraries are very useful tosimplify and to accelerate the multimedia document retrieval. Wecan imagine that we can extract mu...Sound indexing and segmentation of digital documentsespecially in the internet and digital libraries are very useful tosimplify and to accelerate the multimedia document retrieval. Wecan imagine that we can extract multimedia files not only bykeywords but also by speech semantic contents. The maindifficulty of this operation is the parameterization and modellingof the sound track and the discrimination of the speech, musicand noise segments. In this paper, we will present aSpeech/Music/Noise indexing interface designed for audiodiscrimination in multimedia documents. The program uses astatistical method based on ANN and HMM classifiers. After preemphasisand segmentation, the audio segments are analysed bythe cepstral acoustic analysis method. The developed system wasevaluated on a database constituted of music songs with Arabicspeech segments under several noisy environments.展开更多
In this paper, a new method to approximate the compensation term in the Jacobian logarithm used by the MAP decoder is proposed. Using the proposed approximation, the complex functions In（.） and exp（.） in the Exact...In this paper, a new method to approximate the compensation term in the Jacobian logarithm used by the MAP decoder is proposed. Using the proposed approximation, the complex functions In（.） and exp（.） in the Exact-log-MAP algorithm can be estimated with high accuracy and lower computational complexity. The efficacy of the proposed approximation is investigated and demonstrated by applying it to iteratively decoded BICM （Bit Interleaved Coded Modulation）.展开更多
In this paper we propose a new class of ternary Zero Correlation Zone (ZCZ) sequence sets based on binary ZCZ sequence sets construction. It is shown that the proposed ternary ZCZ sequence sets can reach the upper bou...In this paper we propose a new class of ternary Zero Correlation Zone (ZCZ) sequence sets based on binary ZCZ sequence sets construction. It is shown that the proposed ternary ZCZ sequence sets can reach the upper bound on the ZCZ sequences. The performance of the proposed sequences set in asynchronous Direct Sequence-Code Division Multiple Access (DS-CDMA) system is evaluated. In the simulation we used two types of channels: Additive White Gaussian Noise (AWGN) and frequency non-selective fading with AWGN noise. The proposed ternary ZCZ sequence sets show better results, in term of Bit Error Rate (BER), than Hayashi’s ternary ZCZ sequence sets.展开更多
Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these problems.This paper does not propose a new EA,but does construct a new...Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these problems.This paper does not propose a new EA,but does construct a new form of optimization problems.The new optimization formulation has two differences from the common ones.One is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the designed.This difference is beneficial to decrease complexity in some sense.The second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation parameters.This difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are validated.The results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.展开更多
This contribution proposes a new combination symbol mapper/8-ary constellation, which is a joint optimization of an 8-ary signal constellation and its symbol mapping operation, to improve the performance of Bit Interl...This contribution proposes a new combination symbol mapper/8-ary constellation, which is a joint optimization of an 8-ary signal constellation and its symbol mapping operation, to improve the performance of Bit Interleaved Coded Modulation with Iterative Decoding (BICM-ID). The basic idea was to use the so called (1,7) constellation (which is a capacitive efficient constellation) instead of the conventional 8-PSK constellation and to choose the most suitable mapping for it. A comparative study between the combinations most suitable mapping/(1,7) constellation and SSP mapping/conventional 8-PSK constellation has been carried out. Simulation results showed that the 1st combination significantly outperforms the 2nd combination and with only 4 iterations, it gives better performance than the 2nd combination with 8 iterations. A gain of 4 dB is given by iteration 4 of the 1st combination compared to iteration 8 of the 2nd combination at a BER level equal to 10-5, and it (iteration 4 of the 1st combination) can attain a BER equal to 10-7 for, only, a SNR = 5.6 dB.展开更多
Knowledge of the band gap and transmission and reflection spectrum of a photonic crystal is essential elements for their design. A graphical interface that quickly determines the banding pattern and spectrum based on ...Knowledge of the band gap and transmission and reflection spectrum of a photonic crystal is essential elements for their design. A graphical interface that quickly determines the banding pattern and spectrum based on the Plane Wave Method (PWM) and coupled modes method (CMM) respectively is created. It is used to explore the behavior of a Bragg structure with the ability to easily vary the important parameters such as refractive indices, number and thickness of layers.展开更多
In communication alarm correlation analysis,traditional association rules generation(ARG) algorithm usually has low efficiency and high error rate.This paper proposes an alarm correlation rules generation algorithm ba...In communication alarm correlation analysis,traditional association rules generation(ARG) algorithm usually has low efficiency and high error rate.This paper proposes an alarm correlation rules generation algorithm based on the confidence covered value.Confidence covered value method can judge whether a rule is redundant or not scientific After the rules that based on weighted frequent patterns(WFPs) generated,the association rules were deleted by the confidence covered value,in order to delete the redundant rules and keep the rules with more information.Experiments show that the alarm correlation rules generation algorithm based on the confidence covered value has higher efficiency than the traditional method,and can effectively remove redundant rules.Thus it is very suitable for telecommunication alarm association rules processing.展开更多
Intrinsically disordered or unstructured proteins(or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficienc...Intrinsically disordered or unstructured proteins(or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination of intrinsic disorder and the exponential increase of unannotated protein sequences, developing complementary computational prediction methods has been an active area of research for several decades. Here, we employed an ensemble of deep Squeeze-and-Excitation residual inception and long short-term memory(LSTM) networks for predicting protein intrinsic disorder with input from evolutionary information and predicted one-dimensional structural properties. The method, called SPOT-Disorder2, offers substantial and consistent improvement not only over our previous technique based on LSTM networks alone,but also over other state-of-the-art techniques in three independent tests with different ratios of disordered to ordered amino acid residues, and for sequences with either rich or limited evolutionary information. More importantly, semi-disordered regions predicted in SPOT-Disorder2 are more accurate in identifying molecular recognition features(MoRFs) than methods directly designed for MoRFs prediction. SPOT-Disorder2 is available as a web server and as a standalone program at https://sparks-lab.org/server/spot-disorder2/.展开更多
We propose a novel approach called the robust fractional-order proportional-integral-derivative（FOPID）controller, to stabilize a perturbed nonlinear chaotic system on one of its unstable fixed points. The stability ...We propose a novel approach called the robust fractional-order proportional-integral-derivative（FOPID）controller, to stabilize a perturbed nonlinear chaotic system on one of its unstable fixed points. The stability analysis of the nonlinear chaotic system is made based on the proportional-integral-derivative actions using the bifurcation diagram. We extract an initial set of controller parameters, which are subsequently optimized using a quadratic criterion. The integral and derivative fractional orders are also identified by this quadratic criterion. By applying numerical simulations on two nonlinear systems, namely the multi-scroll Chen system and the Genesio-Tesi system,we show that the fractional PI~λD~μ controller provides the best closed-loop system performance in stabilizing the unstable fixed points, even in the presence of random perturbation.展开更多
The objective of this study was to evaluate the effect of modified atmosphere packaging(MAP)on fish skin,gills and intestines bacterial microbiome.Whole gilthead seabream was packed aerobically or under modified atmos...The objective of this study was to evaluate the effect of modified atmosphere packaging(MAP)on fish skin,gills and intestines bacterial microbiome.Whole gilthead seabream was packed aerobically or under modified atmospheres(60%CO_(2),30%N_(2),10%O_(2))and stored isothermally at 0℃.Next Generation Sequencing(NGS)analysis was applied for the characterization of fish microbiome on fish skin,gills,and intestines initially(time of packaging,1 day after harvesting)and after 10 days of isothermal storage at 0℃.NGS results indicated statistically significant differences in families’richness and diversity in the tested fish tissues between aerobic and MAP packaging during storage at 0℃.The most persistent bacteria were Proteobacteria for both packaging types.For fish skin microbiota,the initially prevailing families were Comamonadaceae,Enterobacteriaceae and Moraxellaceae while in the intestines Comamonadaceae,Anaplasmataceae,Bacillaceae and Enterobacteriaceae were the dominant bacteria.At the end of storage period,the fish microbiota was dominated by psychotropic and psychrophilic families(Pseudoalteromonadaceae,Psychromonadaceae,and Shewanellaceae),while families such as Comamonadaceae were persistent under MAP conditions.By 8 days of fish storage at 0℃,МАРsamples exhibited higher sensory scorings than the respective aerobically stored fish,indicating better retention of fish freshness and fish quality attributes under MAP.Based on the results of the study,MAP modified significantly the microbiological status and extended the shelf life of fish.NGS was a powerful tool that provided a more complete assessment compared to a culture-based analysis.展开更多
As a result of noise and intensity non-uniformity,automatic segmentation of brain tissue in magnetic resonance imaging (MRI) is a challenging task.In this study a novel brain MRI segmentation approach is presented whi...As a result of noise and intensity non-uniformity,automatic segmentation of brain tissue in magnetic resonance imaging (MRI) is a challenging task.In this study a novel brain MRI segmentation approach is presented which employs Dempster-Shafer theory (DST) to perform information fusion.In the proposed method,fuzzy c-mean (FCM) is applied to separate features and then the outputs of FCM are interpreted as basic belief structures.The salient aspect of this paper is the interpretation of each FCM output as a belief structure with particular focal elements.The results of the proposed method are evaluated using Dice similarity and Accuracy indices.Qualitative and quantitative comparisons show that our method performs better and is more robust than the existing method.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.62166010)the Guangxi Natural Science Foundation(Grant No.2023GXNSFAA026087).
文摘Hypergraphs can accurately capture complex higher-order relationships,but it is challenging to identify their important nodes.In this paper,an improved PageRank(ImPageRank)algorithm is designed to identify important nodes in a directed hypergraph.The algorithm introduces the Jaccard similarity of directed hypergraphs.By comparing the numbers of common neighbors between nodes with the total number of their neighbors,the Jaccard similarity measure takes into account the similarity between nodes that are not directly connected,and can reflect the potential correlation between nodes.An improved susceptible–infected(SI)model in directed hypergraph is proposed,which considers nonlinear propagation mode and more realistic propagation mechanism.In addition,some important node evaluation methods are transferred from undirected hypergraphs and applied to directed hypergraphs.Finally,the ImPageRank algorithm is used to evaluate the performance of the SI model,network robustness and monotonicity.Simulations of real networks demonstrate the excellent performance of the proposed algorithm and provide a powerful framework for identifying important nodes in directed hypergraphs.
基金supported by Swiss National Science Foundation Grant #205320-101621supported by ONR N00014-03-1-0071
文摘In this paper, we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model. We address the problem of textures where neither the gray-level information nor the boundary information is adequate for object extraction. This is often the case of natural images composed of both homogeneous and textured regions. Because these images cannot be in general directly processed by the gray-level information, we propose a new texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry. Then, we use the popular Kullback-Leibler distance to design an active contour model which distinguishes the background and textures of interest. The existence of a minimizing solution to the proposed segmentation model is proven. Finally, a texture segmentation algorithm based on the Split-Bregrnan method is introduced to extract meaningful objects in a fast way. Promising synthetic and real-world results for gray-scale and color images are presented.
文摘Viterbi decoding is widely used in many radio systems. Because of the large computation complexity, it is usually implemented with ASIC chips, FPGA chips, or optimized hardware accelerators. With the rapid development of the multicore technology, multicore platforms become a reasonable choice for software radio (SR) systems. The Cell Broadband Engine processor is a state-of-art multi-core processor designed by Sony, Toshiba, and IBM. In this paper, we present a 64-state soft input Viterbi decoder for WiMAX SR Baseband system based on the Cell processor. With one Synergistic Processor Element (SPE) of a Cell Processor running at 3.2GHz, our Viterbi decoder can achieve the throughput up to 30Mb/s to decode the tail-biting convolutional code. The performance demonstrates that the proposed Viterbi decoding implementation is very efficient. Moreover, the Viterbi decoder can be easily integrated to the SR system and can provide a highly integrated SR solution. The optimization methodology in this module design can be extended to other modules on Cell platform.
文摘Many studies suggest that EEG signals provide enough information for the detection of human emotions with feature based classification methods. However, very few studies have reported a classification method that reliably works for individual participants (classification accuracy well over 90%). Further, a necessary condition for real life applications is a method that allows, irrespective of the immense individual difference among participants, to have minimal variance over the individual classification accuracy. We conducted offline computer aided emotion classification experiments using strict experimental controls. We analyzed EEG data collected from nine participants using validated film clips to induce four different emotional states (amused, disgusted, sad and neutral). The classification rate was evaluated using both unsupervised and supervised learning algorithms (in total seven “state of the art” algorithms were tested). The largest classification accuracy was computed by means of Support Vector Machine. Accuracy rate was on average 97.2%. The experimental protocol effectiveness was further supported by very small variance among individual participants’ classification accuracy (within interval: 96.7%, 98.3%). Classification accuracy evaluated on reduced number of electrodes suggested, consistently with psychological constructionist approaches, that we were able to classify emotions considering cortical activity from areas involved in emotion representation. The experimental protocol therefore appeared to be a key factor to improve the classification outcome by means of data quality improvements.
基金supported by the National Natural Science Foundation of China(Grant No.61831019).
文摘Generalized cross-correlation is considered as the most straightforward time delay estimation algorithm.Depending on various weighting function,different methods were derived and a straightforward method,named phase transform(PHAT)has been widely used.PHAT is well-known for its robustness to reverberation and its sensitivity to noise,which is partly due to the fact that PHAT distributes same weights to the frequencies dominated by signal or noise.To alleviate this problem,two weighting functions are proposed in this paper.By taking a posteriori signal-to-noise ratio(SNR)into account to classify reliable and unreliable frequencies,different weights could be assigned.The first proposed weighting function borrows the idea of binary mask and distributes same weights to frequencies in same set,whereas,the second one assigns weights based on coherence function.Experiments showed the robustness of proposed methods to reverberation and noise for improving the performance of time delay estimation through various criteria.
文摘There are two key issues in distributed intrusion detection system,that is,maintaining load balance of system and protecting data integrity.To address these issues,this paper proposes a new distributed intrusion detection model for big data based on nondestructive partitioning and balanced allocation.A data allocation strategy based on capacity and workload is introduced to achieve local load balance,and a dynamic load adjustment strategy is adopted to maintain global load balance of cluster.Moreover,data integrity is protected by using session reassemble and session partitioning.The simulation results show that the new model enjoys favorable advantages such as good load balance,higher detection rate and detection efficiency.
文摘In order to assist physically handicapped persons in their movements,we developed an embedded isolated word speech recognition system(ASR)applied to voice control of smart wheelchairs.However,in spite of the existence in the industrial market of several kinds of electric wheelchairs,the problem remains the need to manually control this device by hand via joystick;which limits their use especially by people with severe disabilities.Thus,a significant number of disabled people cannot use a standard electric wheelchair or drive it with difficulty.The proposed solution is to use the voice to control and drive the wheelchair instead of classical joysticks.The intelligent chair is equipped with an obstacle detection system consisting of ultrasonic sensors,a moving navigation algorithm and a speech acquisition and recognition module for voice control embedded in a DSP card.The ASR architecture consists of two main modules.The first one is the speech parameterization module(features extraction)and the second module is the classifier which identifies the speech and generates the control word to motors power unit.The training and recognition phases are based on Hidden Markov Models(HMM),K-means,Baum-Welch and Viterbi algorithms.The database consists of 39 isolated speaker words(13 words pronounced 3 times under different environments and conditions).The simulations are tested under Matlab environment and the real-time implementation is performed by C language with code composer studio embedded in a TMS 320 C6416 DSP kit.The results and experiments obtained gave promising recognition ratio and accuracy around 99%in clean environment.However,the system accuracy decreases considerably in noisy environments,especially for SNR values below 5 dB(in street:78%,in factory:52%).
基金This research is supported by the NationalResearch Council of Thailand(NRCT).NRISS No.906919,144276,2589514(FFB65E0712),2589488(FFB65E0713).
文摘Image classification always has open challenges for computer vision research.Nowadays,deep learning has promoted the development of this field,especially in Convolutional Neural Networks(CNNs).This article proposes the development of efficiently scaled dilation of DropBlock optimization in CNNs for the fungus classification,which there are five species in this experiment.The proposed technique adjusts the convolution size at 35,45,and 60 with the max-polling size 2×2.The CNNs models are also designed in 12 models with the different BlockSizes and KeepProp.The proposed techniques provide maximum accuracy of 98.30%for the training set.Moreover,three accurate models,called Precision,Recall,and F1-score,are employed to measure the testing set.The experiment results expose that the proposed models achieve to classify the fungus and provide an excellent accuracy compared with the previous techniques.Furthermore,the proposed techniques can reduce the CNNs structure layer,directly affecting resource and time computation.
基金supported by the National Natural Science Foundation of China (Grant No.61471014,61231015)
文摘Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of the problem, a soft decision is often used as an optimal technique for speech restoration. In this paper, considering a new fashion of speech and noise models, we present two model-based soft decision techniques. One technique estimates a ratio mask generated by the exact Bayesian estimators of speech and noise. For the second technique, we consider one issue that an optimum local criterion(LC) for a certain SNR may not be appropriate for other SNRs. So we estimate a probabilistic mask with a variable LC. Experimental results show that the proposed method achieves a better performance than reference methods in speech quality.
文摘Sound indexing and segmentation of digital documentsespecially in the internet and digital libraries are very useful tosimplify and to accelerate the multimedia document retrieval. Wecan imagine that we can extract multimedia files not only bykeywords but also by speech semantic contents. The maindifficulty of this operation is the parameterization and modellingof the sound track and the discrimination of the speech, musicand noise segments. In this paper, we will present aSpeech/Music/Noise indexing interface designed for audiodiscrimination in multimedia documents. The program uses astatistical method based on ANN and HMM classifiers. After preemphasisand segmentation, the audio segments are analysed bythe cepstral acoustic analysis method. The developed system wasevaluated on a database constituted of music songs with Arabicspeech segments under several noisy environments.
文摘In this paper, a new method to approximate the compensation term in the Jacobian logarithm used by the MAP decoder is proposed. Using the proposed approximation, the complex functions In（.） and exp（.） in the Exact-log-MAP algorithm can be estimated with high accuracy and lower computational complexity. The efficacy of the proposed approximation is investigated and demonstrated by applying it to iteratively decoded BICM （Bit Interleaved Coded Modulation）.
文摘In this paper we propose a new class of ternary Zero Correlation Zone (ZCZ) sequence sets based on binary ZCZ sequence sets construction. It is shown that the proposed ternary ZCZ sequence sets can reach the upper bound on the ZCZ sequences. The performance of the proposed sequences set in asynchronous Direct Sequence-Code Division Multiple Access (DS-CDMA) system is evaluated. In the simulation we used two types of channels: Additive White Gaussian Noise (AWGN) and frequency non-selective fading with AWGN noise. The proposed ternary ZCZ sequence sets show better results, in term of Bit Error Rate (BER), than Hayashi’s ternary ZCZ sequence sets.
基金Major Project for New Generation of AI under Grant 2018AAA0100400in part by Scientific Research Fund of Hunan Provincial Education Department of China under Grant 21A0350,21C0439+4 种基金in part by the National Natural Science Foundation of China under Grant 61673355in part by the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)under Grant CUGGC02in part by the Hubei Provincial Natural Science Foundation of China under Grant 2015CFA010in part by the high-performance computing platform of the China University of Geosciencesin part by the 111 projectunder Grant B17040.
文摘Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these problems.This paper does not propose a new EA,but does construct a new form of optimization problems.The new optimization formulation has two differences from the common ones.One is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the designed.This difference is beneficial to decrease complexity in some sense.The second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation parameters.This difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are validated.The results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.
文摘This contribution proposes a new combination symbol mapper/8-ary constellation, which is a joint optimization of an 8-ary signal constellation and its symbol mapping operation, to improve the performance of Bit Interleaved Coded Modulation with Iterative Decoding (BICM-ID). The basic idea was to use the so called (1,7) constellation (which is a capacitive efficient constellation) instead of the conventional 8-PSK constellation and to choose the most suitable mapping for it. A comparative study between the combinations most suitable mapping/(1,7) constellation and SSP mapping/conventional 8-PSK constellation has been carried out. Simulation results showed that the 1st combination significantly outperforms the 2nd combination and with only 4 iterations, it gives better performance than the 2nd combination with 8 iterations. A gain of 4 dB is given by iteration 4 of the 1st combination compared to iteration 8 of the 2nd combination at a BER level equal to 10-5, and it (iteration 4 of the 1st combination) can attain a BER equal to 10-7 for, only, a SNR = 5.6 dB.
文摘Knowledge of the band gap and transmission and reflection spectrum of a photonic crystal is essential elements for their design. A graphical interface that quickly determines the banding pattern and spectrum based on the Plane Wave Method (PWM) and coupled modes method (CMM) respectively is created. It is used to explore the behavior of a Bragg structure with the ability to easily vary the important parameters such as refractive indices, number and thickness of layers.
基金Project of Sichuan Provincial Department of Education,China(No.13Z215)the Foundation of Scientific Research of Chengdu University of Information Technology,China(No.J201405)+1 种基金the Project of Sichuan Provincial Department of Science and Technology,China(No.2015JY0047)the Open Research Subject of Key Laboratory of Signal and Information Processing,China(No.szjj 2015-070)
文摘In communication alarm correlation analysis,traditional association rules generation(ARG) algorithm usually has low efficiency and high error rate.This paper proposes an alarm correlation rules generation algorithm based on the confidence covered value.Confidence covered value method can judge whether a rule is redundant or not scientific After the rules that based on weighted frequent patterns(WFPs) generated,the association rules were deleted by the confidence covered value,in order to delete the redundant rules and keep the rules with more information.Experiments show that the alarm correlation rules generation algorithm based on the confidence covered value has higher efficiency than the traditional method,and can effectively remove redundant rules.Thus it is very suitable for telecommunication alarm association rules processing.
基金supported by Australian Research Council (Grant No. DP180102060) to YZ and KPin part by the National Health and Medical Research Council (Grant No. 1121629) of Australia to YZ+1 种基金the High Performance Computing Cluster ‘Gowonda’ to complete this studythe aid of the research cloud resources provided by the Queensland Cyber Infrastructure Foundation (QCIF), Australia.
文摘Intrinsically disordered or unstructured proteins(or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination of intrinsic disorder and the exponential increase of unannotated protein sequences, developing complementary computational prediction methods has been an active area of research for several decades. Here, we employed an ensemble of deep Squeeze-and-Excitation residual inception and long short-term memory(LSTM) networks for predicting protein intrinsic disorder with input from evolutionary information and predicted one-dimensional structural properties. The method, called SPOT-Disorder2, offers substantial and consistent improvement not only over our previous technique based on LSTM networks alone,but also over other state-of-the-art techniques in three independent tests with different ratios of disordered to ordered amino acid residues, and for sequences with either rich or limited evolutionary information. More importantly, semi-disordered regions predicted in SPOT-Disorder2 are more accurate in identifying molecular recognition features(MoRFs) than methods directly designed for MoRFs prediction. SPOT-Disorder2 is available as a web server and as a standalone program at https://sparks-lab.org/server/spot-disorder2/.
基金Project supported by the Ministry of Higher Education and Scientific Research,Algeria(CNEPRU No.A10N01UN210120150002)
文摘We propose a novel approach called the robust fractional-order proportional-integral-derivative（FOPID）controller, to stabilize a perturbed nonlinear chaotic system on one of its unstable fixed points. The stability analysis of the nonlinear chaotic system is made based on the proportional-integral-derivative actions using the bifurcation diagram. We extract an initial set of controller parameters, which are subsequently optimized using a quadratic criterion. The integral and derivative fractional orders are also identified by this quadratic criterion. By applying numerical simulations on two nonlinear systems, namely the multi-scroll Chen system and the Genesio-Tesi system,we show that the fractional PI~λD~μ controller provides the best closed-loop system performance in stabilizing the unstable fixed points, even in the presence of random perturbation.
基金the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-CurieGrant agreement 872217.
文摘The objective of this study was to evaluate the effect of modified atmosphere packaging(MAP)on fish skin,gills and intestines bacterial microbiome.Whole gilthead seabream was packed aerobically or under modified atmospheres(60%CO_(2),30%N_(2),10%O_(2))and stored isothermally at 0℃.Next Generation Sequencing(NGS)analysis was applied for the characterization of fish microbiome on fish skin,gills,and intestines initially(time of packaging,1 day after harvesting)and after 10 days of isothermal storage at 0℃.NGS results indicated statistically significant differences in families’richness and diversity in the tested fish tissues between aerobic and MAP packaging during storage at 0℃.The most persistent bacteria were Proteobacteria for both packaging types.For fish skin microbiota,the initially prevailing families were Comamonadaceae,Enterobacteriaceae and Moraxellaceae while in the intestines Comamonadaceae,Anaplasmataceae,Bacillaceae and Enterobacteriaceae were the dominant bacteria.At the end of storage period,the fish microbiota was dominated by psychotropic and psychrophilic families(Pseudoalteromonadaceae,Psychromonadaceae,and Shewanellaceae),while families such as Comamonadaceae were persistent under MAP conditions.By 8 days of fish storage at 0℃,МАРsamples exhibited higher sensory scorings than the respective aerobically stored fish,indicating better retention of fish freshness and fish quality attributes under MAP.Based on the results of the study,MAP modified significantly the microbiological status and extended the shelf life of fish.NGS was a powerful tool that provided a more complete assessment compared to a culture-based analysis.
文摘As a result of noise and intensity non-uniformity,automatic segmentation of brain tissue in magnetic resonance imaging (MRI) is a challenging task.In this study a novel brain MRI segmentation approach is presented which employs Dempster-Shafer theory (DST) to perform information fusion.In the proposed method,fuzzy c-mean (FCM) is applied to separate features and then the outputs of FCM are interpreted as basic belief structures.The salient aspect of this paper is the interpretation of each FCM output as a belief structure with particular focal elements.The results of the proposed method are evaluated using Dice similarity and Accuracy indices.Qualitative and quantitative comparisons show that our method performs better and is more robust than the existing method.
