Real-time digital image stabilization based on regional field image gray projection

Digital image stabilization technique plays important roles in video surveillance and object acquisition.Many useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,respectively.For the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection curves.Then motion compensations can be obtained after using the Kalman filter method.Finally,the odd field image is adjusted according to the compensations.In the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current frame.By minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be estimated.Therefore,the even field image can be adjusted by combining the inter-field motion parameters and the odd field compensations.Finally,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field images.Experimental results show that the proposed algorithm can run in real-time and have a good stabilization performance.In addition,image blurring can be improved.

A Photonuclear Reaction Model Based on IQMD in Intermediate-Energy Region

A photonuclear reaction transport model based on an isospin-dependent quantum molecular dynamics model （IQMD） is presented in the intermediate energy region, which is named as GiQMD in this study. Methodology to simulate the course of the photonuclear reaction within the IQMD frame is described to study the photo- absorption cross section and π meson production, and the simulation results are compared with some available experimental data as well as the Giessen Boltzmann-Uehling-Uhlenbeck model.

Hybrid Convolutional Neural Network for Plant Diseases Prediction

Plant diseases prediction is the essential technique to prevent the yield loss and gain high production of agricultural products.The monitoring of plant health continuously and detecting the diseases is a significant for sustainable agri-culture.Manual system to monitor the diseases in plant is time consuming and report a lot of errors.There is high demand for technology to detect the plant dis-eases automatically.Recently image processing approach and deep learning approach are highly invited in detection of plant diseases.The diseases like late blight,bacterial spots,spots on Septoria leaf and yellow leaf curved are widely found in plants.These are the main reasons to affects the plants life and yield.To identify the diseases earliest,our research presents the hybrid method by com-bining the region based convolutional neural network(RCNN)and region based fully convolutional networks(RFCN)for classifying the diseases.First the leaf images of plants are collected and preprocessed to remove noisy data in image.Further data normalization,augmentation and removal of background noises are done.The images are divided as testing and training,training images are fed as input to deep learning architecture.First,we identify the region of interest(RoI)by using selective search.In every region,feature of convolutional neural network(CNN)is extracted independently for further classification.The plants such as tomato,potato and bell pepper are taken for this experiment.The plant input image is analyzed and classify as healthy plant or unhealthy plant.If the image is detected as unhealthy,then type of diseases the plant is affected will be displayed.Our proposed technique achieves 98.5%of accuracy in predicting the plant diseases.

Temperature characteristics research of SOI pressure sensor based on asymmetric base region transistor

Based on the asymmetric base region transistor, a pressure sensor with temperature compensation circuit is proposed in this paper. The pressure sensitive structure of the proposed sensor is constructed by a C-type silicon cup and a Wheatstone bridge with four piezoresistors（R_1, R_2, R_3 and R_4/locating on the edge of a square silicon membrane. The chip was designed and fabricated on a silicon on insulator（SOI） wafer by micro electromechanical system（MEMS） technology and bipolar transistor process. When the supply voltage is 5.0 V, the corresponding temperature coefficient of the sensitivity（TCS） for the sensor before and after temperature compensation are -1862 and -1067 ppm/℃, respectively. Through varying the ratio of the base region resistances r_1 and r_2, the TCS for the sensor with the compensation circuit is -127 ppm/℃. It is possible to use this compensation circuit to improve the temperature characteristics of the pressure sensor.

Region stepwise reconstruction method based on two source–detector-separation groups for reconstructing background optical properties of two-layered slab sample

The accuracy of the background optical properties has a considerable effect on the quality of reconstructed images in near-infrared functional brain imaging based on continuous wave diffuse optical tomography（CW-DOT）. We propose a region stepwise reconstruction method in CW-DOT scheme for reconstructing the background absorption and reduced scattering coefficients of the two-layered slab sample with the known geometric information. According to the relation between the thickness of the top layer and source– detector separation, the conventional measurement data are divided into two groups and are employed to reconstruct the top and bottom background optical properties, respectively. The numerical simulation results demonstrate that the proposed method can reconstruct the background optical properties of two-layered slab sample effectively. The region-of-interest reconstruction results are better than those of the conventional simultaneous reconstruction method.

Computing a ground appropriateness index for route selection in permafrost regions

The reasonable calculation of ground appropriateness index in permafrost region is the precondition of highway route design in permafrost region. The theory of knowledge base and fuzzy mathematics are applied, and the damage effect of permafrost is considered in the paper. Based on the idea of protecting permafrost the calculation method of ground appro- priateness index is put forward. Firstly, based on the actual environment conditions, the paper determines the factors affecting the road layout in permafrost areas by qualitative and quantitative analysis, including the annual slope, the average annual ground temperature of permafrost, the amount of ice in frozen soil, and the interference engineering. Secondly, based on the knowledge base theory and the use of Delphi method, the paper establishes the knowledge base, the rule base of the permafrost region and inference mechanism. The method of selecting the road in permafrost region is completed and realized by using the software platform. Thirdly, taking the Tuotuo River to Kaixin Mountain section of permafrost region as an example, the application of the method is studied by using an ArcGIS platform. Results show that the route plan determined by the method of selecting the road in perma-frost region can avoid the high temperature and high ice content area, conform the terrain changes and evade the heat disturbance among the existing projects. A reasonable route plan can be achieved, and it can provide the basis for the next engineering construction.

Long round-sharp needle release technique for 34 cases of superior cluneal nerve entrapment syndrome

Objective:To observe the clinical effect on superior cluneal nerve(SCN)entrapment syndrome treated with the release technique of long round-sharp needle.Methods:The syndrome differentiation based on meridian muscle region was adopted.The release technique of the long round-sharp needle was used at the lesions of meridian tendon region,Yāoyícì(Beside Yaoyi)and the transverse process of the third lumbar vertebra in 34 patients with SCN entrapment syndrome.The treatment was given once a week,4 treatments made one course.After one course treatment,the therapeutic effect was observed.The results of pain rating index(PRI),the visual analogy scores(VAS)and the present pain intensity(PPI)were compared before and after treatment.Results:Of 34 patients,28 cases(82%)were cured,6 cases(18%)effective and 0 case(0%)failed.The total effective rate was 100%.The scores of PRI,VAS and PPI were(10.78±1.98),(5.98±1.19)and(3.91±1.68)successively in 34 cases before treatment and they were(1.98±1.79),(0.89±1.12)and(0.82±0.79)after treatment.The score of every evaluation scale after treatment was lower significantly than that before treatment(all P<0.01).Conclusion:The release technique of long round-sharp needle achieves the satisfactory clinical effect on SCN entrapment syndrome.Hence,this therapeutic method deserves to be promoted.