The extraction of potassium from a tablet mixture of K-feldspar ore and CaSO4by roasting was studied with a focus on the effects of the decomposition behavior of CaSO4on the potassium extraction process.The roasted sl...The extraction of potassium from a tablet mixture of K-feldspar ore and CaSO4by roasting was studied with a focus on the effects of the decomposition behavior of CaSO4on the potassium extraction process.The roasted slags were characterized by X-ray diffraction（XRD）,scanning electron microscopy（SEM）,energy-dispersive X-ray spectroscopy,and thermogravimetric（TG）analysis.The XRD analysis revealed that hydrosoluble mischcrystal K2Ca2（SO4）3was obtained by ion exchange of Ca^2＋ in CaSO4 and K^＋ in KAlSi3O8.Meanwhile,the intermediate product,SiO2,separated from KAl Si3O8and reacted with CaSO4to decompose CaSO4.The SEM results showed that some blowholes emerged on the surface of the CaSO4particles when they reacted with SiO2at 1200℃,which indicates that SO2and O2gases were released from CaSO4.The TG curves displayed that pure CaSO4could not be decomposed below 1200℃,while the mixture of K-feldspar ore and CaSO4began to lose weight at 1000℃.The extraction rate of potassium and decomposition rate of CaSO4were 62%and 44%,respectively,at a mass ratio of CaSO4to K-feldspar ore of 3：1,temperature of 1200℃,tablet-forming pressure of6 MPa,and roasting time of 2 h.The decomposition of CaSO4reduced the potassium extraction rate;therefore,the required amount of CaSO4was more than the theoretical amount.However,excess CaSO4was also undesirable for the potassium extraction reaction because a massive amount of SO2and O2gas were derived from the decomposition of CaSO4,which provided poor contact between the reactants.The SO2released from CaSO4decomposition can be effectively recycled.展开更多
Polar coded sparse code multiple access(SCMA) system is conceived in this paper. A simple but new iterative multiuser detection framework is proposed, which consists of a message passing algorithm(MPA) based multiuser...Polar coded sparse code multiple access(SCMA) system is conceived in this paper. A simple but new iterative multiuser detection framework is proposed, which consists of a message passing algorithm(MPA) based multiuser detector and a soft-input soft-output(SISO) successive cancellation(SC) polar decoder. In particular, the SISO polar decoding process is realized by a specifically designed soft re-encoder, which is concatenated to the original SC decoder. This soft re-encoder is capable of reconstructing the soft information of the entire polar codeword based on previously detected log-likelihood ratios(LLRs) of information bits. Benefiting from the soft re-encoding algorithm, the resultant iterative detection strategy is able to obtain a salient coding gain. Our simulation results demonstrate that significant improvement in error performance is achieved by the proposed polar-coded SCMA in additive white Gaussian noise(AWGN) channels, where the performance of the conventional SISO belief propagation(BP) polar decoder aided SCMA, the turbo coded SCMA and the low-density parity-check(LDPC) coded SCMA are employed as benchmarks.展开更多
We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary, image of zip code box and message of the two charact...We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary, image of zip code box and message of the two characters binary image： analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements.展开更多
The Wyner-Ziv distributed video coding scheme is characterized for its intraframe encoder and interframe decoder which can also approach the efficiency of an interframe encoder-decoder system. In Wyner-Ziv residual co...The Wyner-Ziv distributed video coding scheme is characterized for its intraframe encoder and interframe decoder which can also approach the efficiency of an interframe encoder-decoder system. In Wyner-Ziv residual coding of video, the residual of a frame with respect to a reference frame is Wyner-Ziv encoded, which can reduces the input entropy and leads to a higher coding efficiency than directly encoding the original frame. In this paper, we propose a new approach of residual coding combined with Region Of Interest (ROI) extraction. Experimental results show that, the proposed scheme achieves better rate-distortion performance compared to conventional Wyner-Ziv coding scheme.展开更多
Weak feature extraction is of great importance for condition monitoring and intelligent diagnosis of aeroengine.Aimed at achieving intelligent diagnosis of aero-engine main shaft bearing,an enhanced sparsity-assisted ...Weak feature extraction is of great importance for condition monitoring and intelligent diagnosis of aeroengine.Aimed at achieving intelligent diagnosis of aero-engine main shaft bearing,an enhanced sparsity-assisted intelligent condition monitoring method is proposed in this paper.Through analyzing the weakness of convex sparse model,i.e.the tradeoff between noise reduction and feature reconstruction,this paper proposes an enhanced-sparsity nonconvex regularized convex model based on Moreau envelope to achieve weak feature extraction.Accordingly,a sparsity-assisted deep convolutional variational autoencoders network is proposed,which achieves the intelligent identification of fault state through training denoised normal data.Finally,the effectiveness of the proposed method is verified through aero-engine bearing run-to-failure experiment.The comparison results show that the proposed method is good at abnormal pattern recognition,showing a good potential for weak fault intelligent diagnosis of aero-engine main shaft bearings.展开更多
We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characte...We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characters binary image; analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements.展开更多
The explosive growth ofmalware variants poses a major threat to information security. Traditional anti-virus systems based on signatures fail to classify unknown malware into their corresponding families and to detect...The explosive growth ofmalware variants poses a major threat to information security. Traditional anti-virus systems based on signatures fail to classify unknown malware into their corresponding families and to detect new kinds of malware pro- grams. Therefore, we propose a machine learning based malware analysis system, which is composed of three modules： data processing, decision making, and new malware detection. The data processing module deals with gray-scale images, Opcode n-gram, and import fimctions, which are employed to extract the features of the malware. The decision-making module uses the features to classify the malware and to identify suspicious malware. Finally, the detection module uses the shared nearest neighbor （SNN） clustering algorithm to discover new malware families. Our approach is evaluated on more than 20 000 malware instances, which were collected by Kingsoft, ESET NOD32, and Anubis. The results show that our system can effectively classify the un- known malware with a best accuracy of 98.9%, and successfully detects 86.7% of the new malware.展开更多
基金Supported by the National Key Research and Development Program(2016YFB0600904)Sichuan Province Science and Technology Project(2017GZ0377)Sichuan University Postdoctoral Research and Development Fund(2017SCU12017)
文摘The extraction of potassium from a tablet mixture of K-feldspar ore and CaSO4by roasting was studied with a focus on the effects of the decomposition behavior of CaSO4on the potassium extraction process.The roasted slags were characterized by X-ray diffraction（XRD）,scanning electron microscopy（SEM）,energy-dispersive X-ray spectroscopy,and thermogravimetric（TG）analysis.The XRD analysis revealed that hydrosoluble mischcrystal K2Ca2（SO4）3was obtained by ion exchange of Ca^2＋ in CaSO4 and K^＋ in KAlSi3O8.Meanwhile,the intermediate product,SiO2,separated from KAl Si3O8and reacted with CaSO4to decompose CaSO4.The SEM results showed that some blowholes emerged on the surface of the CaSO4particles when they reacted with SiO2at 1200℃,which indicates that SO2and O2gases were released from CaSO4.The TG curves displayed that pure CaSO4could not be decomposed below 1200℃,while the mixture of K-feldspar ore and CaSO4began to lose weight at 1000℃.The extraction rate of potassium and decomposition rate of CaSO4were 62%and 44%,respectively,at a mass ratio of CaSO4to K-feldspar ore of 3：1,temperature of 1200℃,tablet-forming pressure of6 MPa,and roasting time of 2 h.The decomposition of CaSO4reduced the potassium extraction rate;therefore,the required amount of CaSO4was more than the theoretical amount.However,excess CaSO4was also undesirable for the potassium extraction reaction because a massive amount of SO2and O2gas were derived from the decomposition of CaSO4,which provided poor contact between the reactants.The SO2released from CaSO4decomposition can be effectively recycled.
基金supported in part by National Natural Science Foundation of China (no. 61571373, no. 61501383, no. U1734209, no. U1709219)in part by Key International Cooperation Project of Sichuan Province (no. 2017HH0002)+2 种基金in part by Marie Curie Fellowship (no. 792406)in part by the National Science and Technology Major Project under Grant 2016ZX03001018-002in part by NSFC China-Swedish project (no. 6161101297)
文摘Polar coded sparse code multiple access(SCMA) system is conceived in this paper. A simple but new iterative multiuser detection framework is proposed, which consists of a message passing algorithm(MPA) based multiuser detector and a soft-input soft-output(SISO) successive cancellation(SC) polar decoder. In particular, the SISO polar decoding process is realized by a specifically designed soft re-encoder, which is concatenated to the original SC decoder. This soft re-encoder is capable of reconstructing the soft information of the entire polar codeword based on previously detected log-likelihood ratios(LLRs) of information bits. Benefiting from the soft re-encoding algorithm, the resultant iterative detection strategy is able to obtain a salient coding gain. Our simulation results demonstrate that significant improvement in error performance is achieved by the proposed polar-coded SCMA in additive white Gaussian noise(AWGN) channels, where the performance of the conventional SISO belief propagation(BP) polar decoder aided SCMA, the turbo coded SCMA and the low-density parity-check(LDPC) coded SCMA are employed as benchmarks.
文摘We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary, image of zip code box and message of the two characters binary image： analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements.
基金Supported by the National Natural Science Foundation of China (No.61003236, 61171053, 61170065)the Doctoral Fund of Ministry of Education of China (No.20113223110002)the Natural Science Major Program for Colleges and Universities in Jiangsu Province(No.11KJA520001)
文摘The Wyner-Ziv distributed video coding scheme is characterized for its intraframe encoder and interframe decoder which can also approach the efficiency of an interframe encoder-decoder system. In Wyner-Ziv residual coding of video, the residual of a frame with respect to a reference frame is Wyner-Ziv encoded, which can reduces the input entropy and leads to a higher coding efficiency than directly encoding the original frame. In this paper, we propose a new approach of residual coding combined with Region Of Interest (ROI) extraction. Experimental results show that, the proposed scheme achieves better rate-distortion performance compared to conventional Wyner-Ziv coding scheme.
基金the National Natural Science Foundations of China(Nos.91860125,51705398)the National Key Basic Research Program of China(No.2015CB057400)the Shaanxi Province 2020 Natural Science Basic Research Plan(No.2020JQ-042).
文摘Weak feature extraction is of great importance for condition monitoring and intelligent diagnosis of aeroengine.Aimed at achieving intelligent diagnosis of aero-engine main shaft bearing,an enhanced sparsity-assisted intelligent condition monitoring method is proposed in this paper.Through analyzing the weakness of convex sparse model,i.e.the tradeoff between noise reduction and feature reconstruction,this paper proposes an enhanced-sparsity nonconvex regularized convex model based on Moreau envelope to achieve weak feature extraction.Accordingly,a sparsity-assisted deep convolutional variational autoencoders network is proposed,which achieves the intelligent identification of fault state through training denoised normal data.Finally,the effectiveness of the proposed method is verified through aero-engine bearing run-to-failure experiment.The comparison results show that the proposed method is good at abnormal pattern recognition,showing a good potential for weak fault intelligent diagnosis of aero-engine main shaft bearings.
文摘We propose a binarization method based pigment in the ZIP code of 24 bmp image simulation and digital identification by CCD sensors, were extracted the grid binary image of zip code box and message of the two characters binary image; analyze the image processing, which includes code frame edge detection and separation of the image binarization, denoising smoothing, tilt correction, the extraction code number, position, normalization processing, digital image thinning, character recognition feature extraction. Through testing, the recognition rate of this method can be over 90%. The recognition time of characters for character is less than 1.3 second, which means the method is of more effective recognition ability and can better satisfy the real system requirements.
基金Project supported by the Natiooal Natural Science Foundation of China （No. 61303264） and the National Basic Research Program （973） of China （Nos. 2012CB315906 and 0800065111001）
文摘The explosive growth ofmalware variants poses a major threat to information security. Traditional anti-virus systems based on signatures fail to classify unknown malware into their corresponding families and to detect new kinds of malware pro- grams. Therefore, we propose a machine learning based malware analysis system, which is composed of three modules： data processing, decision making, and new malware detection. The data processing module deals with gray-scale images, Opcode n-gram, and import fimctions, which are employed to extract the features of the malware. The decision-making module uses the features to classify the malware and to identify suspicious malware. Finally, the detection module uses the shared nearest neighbor （SNN） clustering algorithm to discover new malware families. Our approach is evaluated on more than 20 000 malware instances, which were collected by Kingsoft, ESET NOD32, and Anubis. The results show that our system can effectively classify the un- known malware with a best accuracy of 98.9%, and successfully detects 86.7% of the new malware.
