People consume tea brewed from the leaves of the Camellia sinensis plant for about 50 centuries. Health benefits of the tea have been investigated for about three decades. Especially green tea shows antitoxic and lots...People consume tea brewed from the leaves of the Camellia sinensis plant for about 50 centuries. Health benefits of the tea have been investigated for about three decades. Especially green tea shows antitoxic and lots of properties with its determined ingredients. Turkey is not only the one of the best consumer and but also good producer of the tea as being 5 th producer all over the world. It grows eastern region of the Turkey and high quality tea is imported and exported. To have quality tea, grooving soils are also crucial. In the current research, Tea leaves and their own grown soils were collected from 20 stations where the most tea producer cities as Trabzon, Rize and Artvin tea fields of the eastern of Black Sea Region in Turkey. The cultivated tea and their own grown soil samples were analysed by using EDXRF Spectrometry. In the soil samples, the elements Mg, Al, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Sr, Ba, Pb on percent level and the elements Mg, Al, Si, P, Cl, K, Ca, Ti, Mn, Fe, Ni, Cu, Zn and Sr in the tea leaves were detected by using SKRAY 3600-EDXRF.and also the obtained data were evaluated with the Kriging interpolation of geostatistical method. Element content were investigated in the soil and tea samples according to the geological situations and also the relation of elemental difference between the tea and the own grown soil. Pb/Zn ratio was also anaysed in the samples.展开更多
When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competitio...When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competition strategy algorithm” is presented. In this method, initial measurements give birth to several particle groups around them, regularly. Each of the groups is tested several times, separately, in the beginning periods, and the group that has the most number of efficient particles is selected as the initial particles. For this method, sample initial particles selected are on the basis of several measurements instead of only one first measurement, which surely improves the accuracy of initial particles. The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greatly improves the accuracy of initial particles, which makes the effect of filtering much better.展开更多
The limited physical size for autonomous underwater vehicles （AUV） or unmanned underwater vehicles （UUV） makes it difficult to acquire enough space gain for localizing long-distance targets. A new technique about ...The limited physical size for autonomous underwater vehicles （AUV） or unmanned underwater vehicles （UUV） makes it difficult to acquire enough space gain for localizing long-distance targets. A new technique about long-distance target apperception with passive synthetic aperture array for underwater vehicles is presented. First, a synthetic aperture-processing algorithm based on the FFT transform in the beam space （BSSAP） is introduced. Then, the study on the flank array passive long-distance apperception techniques in the frequency scope of 11-18 kHz is implemented from the view of improving array gains, detection probability and augmenting detected range under a certain sea environment. The results show that the BSSAP algorithm can extend the aperture effectively and improve detection probability. Because of the augment of the transmission loss, the detected range has the trend of decline with the increase of frequency under the same target source level. The synthesized array could improve the space gain by nearly 7 dB and SNR is increased by about 5 dB. The detected range is enhanced to nearly 2 km under the condition of 108-118 dB of the target source level for AUV system in measurement interval of nearly 1 s.展开更多
In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself （including fuzziness, randomness, incompleteness as well as ...In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself （including fuzziness, randomness, incompleteness as well as roughness, etc）. Hence it requires investigating the problem of uncertain information fusion. Robust learning algorithm which adapts to complex environment and the fuzzy inference algorithm which disposes fuzzy information are explored to solve the problem. Based on the fusion technology of neural networks and fuzzy inference algorithm, a multi-sensor uncertain information fusion system is modeled. Also RANFIS learning algorithm and fusing weight synthesized inference algorithm are developed from the ANFIS algorithm according to the concept of robust neural networks. This fusion system mainly consists of RANFIS confidence estimator, fusing weight synthesized inference knowledge base and weighted fusion section. The simulation result demonstrates that the proposed fusion model and algorithm have the capability of uncertain information fusion, thus is obviously advantageous compared with the conventional Kalman weighted fusion algorithm.展开更多
The basic scheme of the orientation detection system using L-shape reticle is introduced. The dimension of the patterns on the reticle of the system in practical applications is designed and an analysis of the princip...The basic scheme of the orientation detection system using L-shape reticle is introduced. The dimension of the patterns on the reticle of the system in practical applications is designed and an analysis of the principle of abstracting the orientation information of the target and the effects and formation method of self-adapting tracking gate is presented. The research result shows that the orientation detection system using L-shape reticle has a good effect on space-filtering, the signals that the orientation detection system sends out are easy to be processed by computer, its self-adapting tracking gate has a strong anti-interference ability, and the whole system＇s searching and tracking performances are quite high.展开更多
文摘People consume tea brewed from the leaves of the Camellia sinensis plant for about 50 centuries. Health benefits of the tea have been investigated for about three decades. Especially green tea shows antitoxic and lots of properties with its determined ingredients. Turkey is not only the one of the best consumer and but also good producer of the tea as being 5 th producer all over the world. It grows eastern region of the Turkey and high quality tea is imported and exported. To have quality tea, grooving soils are also crucial. In the current research, Tea leaves and their own grown soils were collected from 20 stations where the most tea producer cities as Trabzon, Rize and Artvin tea fields of the eastern of Black Sea Region in Turkey. The cultivated tea and their own grown soil samples were analysed by using EDXRF Spectrometry. In the soil samples, the elements Mg, Al, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Sr, Ba, Pb on percent level and the elements Mg, Al, Si, P, Cl, K, Ca, Ti, Mn, Fe, Ni, Cu, Zn and Sr in the tea leaves were detected by using SKRAY 3600-EDXRF.and also the obtained data were evaluated with the Kriging interpolation of geostatistical method. Element content were investigated in the soil and tea samples according to the geological situations and also the relation of elemental difference between the tea and the own grown soil. Pb/Zn ratio was also anaysed in the samples.
基金the National Natural Science Foundation of China (60572038).
文摘When particle filter is applied in radar target tracking, the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles, a new method called “competition strategy algorithm” is presented. In this method, initial measurements give birth to several particle groups around them, regularly. Each of the groups is tested several times, separately, in the beginning periods, and the group that has the most number of efficient particles is selected as the initial particles. For this method, sample initial particles selected are on the basis of several measurements instead of only one first measurement, which surely improves the accuracy of initial particles. The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greatly improves the accuracy of initial particles, which makes the effect of filtering much better.
文摘The limited physical size for autonomous underwater vehicles （AUV） or unmanned underwater vehicles （UUV） makes it difficult to acquire enough space gain for localizing long-distance targets. A new technique about long-distance target apperception with passive synthetic aperture array for underwater vehicles is presented. First, a synthetic aperture-processing algorithm based on the FFT transform in the beam space （BSSAP） is introduced. Then, the study on the flank array passive long-distance apperception techniques in the frequency scope of 11-18 kHz is implemented from the view of improving array gains, detection probability and augmenting detected range under a certain sea environment. The results show that the BSSAP algorithm can extend the aperture effectively and improve detection probability. Because of the augment of the transmission loss, the detected range has the trend of decline with the increase of frequency under the same target source level. The synthesized array could improve the space gain by nearly 7 dB and SNR is increased by about 5 dB. The detected range is enhanced to nearly 2 km under the condition of 108-118 dB of the target source level for AUV system in measurement interval of nearly 1 s.
基金This project was supported by the National Natural Science Foundation of China (60572038)
文摘In practical multi-sensor information fusion systems, there exists uncertainty about the network structure, active state of sensors, and information itself （including fuzziness, randomness, incompleteness as well as roughness, etc）. Hence it requires investigating the problem of uncertain information fusion. Robust learning algorithm which adapts to complex environment and the fuzzy inference algorithm which disposes fuzzy information are explored to solve the problem. Based on the fusion technology of neural networks and fuzzy inference algorithm, a multi-sensor uncertain information fusion system is modeled. Also RANFIS learning algorithm and fusing weight synthesized inference algorithm are developed from the ANFIS algorithm according to the concept of robust neural networks. This fusion system mainly consists of RANFIS confidence estimator, fusing weight synthesized inference knowledge base and weighted fusion section. The simulation result demonstrates that the proposed fusion model and algorithm have the capability of uncertain information fusion, thus is obviously advantageous compared with the conventional Kalman weighted fusion algorithm.
文摘The basic scheme of the orientation detection system using L-shape reticle is introduced. The dimension of the patterns on the reticle of the system in practical applications is designed and an analysis of the principle of abstracting the orientation information of the target and the effects and formation method of self-adapting tracking gate is presented. The research result shows that the orientation detection system using L-shape reticle has a good effect on space-filtering, the signals that the orientation detection system sends out are easy to be processed by computer, its self-adapting tracking gate has a strong anti-interference ability, and the whole system＇s searching and tracking performances are quite high.
