Data processing method for aerial testing of rotating accelerometer gravity gradiometer

A novel method for noise removal from the rotating accelerometer gravity gradiometer(MAGG)is presented.It introduces a head-to-tail data expansion technique based on the zero-phase filtering principle.A scheme for determining band-pass filter parameters based on signal-to-noise ratio gain,smoothness index,and cross-correlation coefficient is designed using the Chebyshev optimal consistent approximation theory.Additionally,a wavelet denoising evaluation function is constructed,with the dmey wavelet basis function identified as most effective for processing gravity gradient data.The results of hard-in-the-loop simulation and prototype experiments show that the proposed processing method has shown a 14%improvement in the measurement variance of gravity gradient signals,and the measurement accuracy has reached within 4E,compared to other commonly used methods,which verifies that the proposed method effectively removes noise from the gradient signals,improved gravity gradiometry accuracy,and has certain technical insights for high-precision airborne gravity gradiometry.

A review of functional MRI application for brain research of Chinese language processing

As one of the most widely used languages in the world,Chinese language is distinct from most western languages in many properties,thus providing a unique opportunity for understanding the brain basis of human language and cognition.In recent years,non-invasive neuroimaging techniques such as magnetic resonance imaging(MRI)blaze a new trail to comprehensively study specific neural correlates of Chinese language processing and Chinese speakers.We reviewed the application of functional MRI(fMRI)in such studies and some essential findings on brain systems in processing Chinese.Specifically,for example,the application of task fMRI and resting-state fMRI in observing the process of reading and writing the logographic characters and producing or listening to the tonal speech.Elementary cognitive neuroscience and several potential research directions around brain and Chinese language were discussed,which may be informative for future research.

Phosphatidylserine:An overview on functionality,processing techniques,patents,and prospects

Phosphatidylserine(PS)is the part of cell structure in the body and has many beneficial functions especially in brain-related aging diseases.Although daily foods can provide PS to human body,the amount is very limited due to its poverty in most foods.To overcome the issue,numerous studies based on PS have been reported to develop PS-related supplements.In this review,PS was comprehensively and critically reviewed from the view of resources,functions,processing techniques,patents,and prospects.For resources,animal,plant,and microorganism origins were all covered with their differences in composition profiles.For functions,benefits regarding memory,cognitive enhancement,exercise performance,reducing Alzheimer’s disease,and attention-deficit hyperactivity disorder symptoms were covered as well as the functional differences among animal-,plant-,and microorganism-based PS-related supplements.For processing techniques,traditional extracting methods from animal,plant,and microorganism tissues were comparatively discussed with enzymatic synthesis based on different reaction systems.Finally,patents of PS-related supplements were evaluated as well as their applications.This review could provide scientific and valuable support for PS industry.

Emotion processing in Parkinson's disease: a blood oxygenation level-dependent functional magnetic resonance imaging study

Parkinson's disease is a neurodegenerative disorder caused by loss of dopamine neurons in the substantia nigra pars compacta. Tremor, rigidity, and bradykinesia are the major symptoms of the disease. These motor impairments are often accompanied by affective and emotional dysfunctions which have been largely studied over the last decade. The aim of this study was to investigate emotional processing organization in the brain of patients with Parkinson's disease and to explore whether there are differences between recognition of different types of emotions in Parkinson's disease. We examined 18 patients with Parkinson's disease(8 men, 10 women) with no history of neurological or psychiatric comorbidities. All these patients underwent identical brain blood oxygenation level-dependent functional magnetic resonance imaging for emotion evaluation. Blood oxygenation level-dependent functional magnetic resonance imaging results revealed that the occipito-temporal cortices, insula, orbitofrontal cortex, basal ganglia, and parietal cortex which are involved in emotion processing, were activated during the functional control. Additionally, positive emotions activate larger volumes of the same anatomical entities than neutral and negative emotions. Results also revealed that Parkinson's disease associated with emotional disorders are increasingly recognized as disabling as classic motor symptoms. These findings help clinical physicians to recognize the emotional dysfunction of patients with Parkinson's disease.

Board-invited review: Sensitivity and responses of functional groups to feed processing methods on a molecular basis

In complex feed structures, there exist main chemical functional groups which are associated with nutrient utilization and availability and functionality. Each functional group has unique molecular structure therefore produce unique molecular vibration spectral profile. Feed processing has been used to improve nutrient utilization for many years. However, to date, there was little study on processing-induced changes of feed intrinsic structure and functional groups on a molecular basis within intact tissue. This is because limited research technique is available to study inherent structure on a molecular basis. Recently bioanalytical techniques： such as Synchrotron Infrared Microspectroscopy as well as Diffuse Reflectance Infrared Fourier Transform molecular spectroscopy have been developed. These techniques enable to detect molecular structure change within intact tissues. These techniques can prevent destruction or alteration of the intrinsic protein structures during processing for analysis. However, these techniques have not been used in animal feed and nutrition research. The objective of this review was show that with the advanced technique, sensitivity and responses of functional groups to feed processing on a molecular basis could be detected in my research team. These functional groups are highly associated with nutrient utilization in animals.

Neural basis of Chinese phonological processing under picture stimulus A functional magnetic resonance imaging study

Studies concerning phonological processing mainly use written stimuli. Functional magnetic resonance imaging was used to investigate the brain regions related to the phonological processing under the picture stimulus in the rhyme task of Chinese language. Results of the test in 13 healthy college students whose native language is Chinese showed the extensive activation in the frontal lobe, parietal lobe and the occipitotemporal cortex, including the inferior frontal gyrus, middle frontal gyrus, supramarginal gyrus and medial occipitotemporal gyrus under the picture stimuli. Moreover, phonological processing induced activation in the superior temporal gyrus （BA 22） under the picture stimuli, but activation was not found in the middle temporal gyrus.

Multi-output Gaussian Process Regression Model with Combined Kernel Function for Polyester Esterification Processes

In polyester fiber industrial processes,the prediction of key performance indicators is vital for product quality.The esterification process is an indispensable step in the polyester polymerization process.It has the characteristics of strong coupling,nonlinearity and complex mechanism.To solve these problems,we put forward a multi-output Gaussian process regression(MGPR)model based on the combined kernel function for the polyester esterification process.Since the seasonal and trend decomposition using loess(STL)can extract the periodic and trend characteristics of time series,a combined kernel function based on the STL and the kernel function analysis is constructed for the MGPR.The effectiveness of the proposed model is verified by the actual polyester esterification process data collected from fiber production.

Characterization of aluminum based functionally graded composites developed via friction stir processing

Al/SiC functionally graded material(FGM) was developed through a novel multi-step friction stir processing(FSP) method. Si C particles with a mean size of 27.5 μm were embedded in the groove on the 6082-Al plate. To create a graded structure over a predefined value, FSP was carried out with three tools with different pin lengths and with varying volume fractions of SiC particles. The structure was formed by passing tools with 1-3 passes with a constant rotational and traveling speeds of 900 r/min and 20 mm/min, respectively. The experiments were conducted at room temperature. Microstructural features of functionally graded(FG) samples were examined by using scanning electron microscopy(SEM) and 3D light microscopy. Mechanical properties in terms of wear resistance and microhardness were thoroughly assessed. The results indicate that the increase in FSP pass number causes more uniform SiC particle dispersion. The microhardness values were impacted by the number of passes and improved by 51.54% for Pass 3 when compared to as-received 6082-Al. Wear resistance of Al/SiC FG samples was found to increase as a result of the addition of SiC particles.

“Toolbox”for the Processing of Functional Polymer Composites

Functional polymer composites(FPCs)have attracted increasing attention in recent decades due to their great potential in delivering a wide range of functionalities.These functionalities are largely determined by functional fillers and their network morphology in polymer matrix.In recent years,a large number of studies on morphology control and interfacial modification have been reported,where numerous preparation methods and exciting performance of FPCs have been reported.Despite the fact that these FPCs have many similarities because they are all consisting of functional inorganic fillers and polymer matrices,review on the overall progress of FPCs is still missing,and especially the overall processing strategy for these composites is urgently needed.Herein,a"Toolbox"for the processing of FPCs is proposed to summarize and analyze the overall processing strategies and corresponding morphology evolution for FPCs.From this perspective,the morphological control methods already utilized for various FPCs are systematically reviewed,so that guidelines or even predictions on the processing strategies of various FPCs as well as multi-functional polymer composites could be given.This review should be able to provide interesting insights for the field of FPCs and boost future intelligent design of various FPCs.

New WA-system of kravchenko functions in digital signal processing

On the basis of modified atomic transformations the new WA-systems of Kravchenko functions are constructed.As an example the digital processing of time series of the various physical nature processing is considered.The numerical experiments and physical analysis of the results confirm the efficiency of the proposed WA-systems of Kravchenko functions.

Training of Multi-layered Neural Network for Data Enlargement Processing Using an Activity Function

In this paper, we present a study on activity functions for an MLNN (multi-layered neural network) and propose a suitable activity function for data enlargement processing. We have carefully studied the training performance of Sigmoid, ReLu, Leaky-ReLu and L & exp. activity functions for few inputs to multiple output training patterns. Our MLNNs model has L hidden layers with two or three inputs to four or six outputs data variations by BP (backpropagation) NN (neural network) training. We focused on the multi teacher training signals to investigate and evaluate the training performance in MLNNs to select the best and good activity function for data enlargement and hence could be applicable for image and signal processing (synaptic divergence) along with the proposed methods with convolution networks. We specifically used four activity functions from which we found out that L & exp. activity function can suite DENN (data enlargement neural network) training since it could give the highest percentage training abilities compared to the other activity functions of Sigmoid, ReLu and Leaky-ReLu during simulation and training of data in the network. And finally, we recommend L & exp. function to be good for MLNNs and may be applicable for signal processing of data and information enlargement because of its performance training characteristics with multiple teacher training patterns using original generated data and hence can be tried with CNN (convolution neural networks) of image processing.

THE EXTREMES OF DEPENDENT CHI-PROCESSES ATTRACTED BY THE BROWN-RESNICK PROCESS

Motivated by some recent works on the topic of the Brown-Resnick process, we study the functional limit theorem for normalized pointwise maxima of dependent chi-processes. It is proven that the properly normalized pointwise maxima of those processes are attracted by the Brown-Resnick process.

Service Function Chain Deployment Algorithm Based on Multi-Agent Deep Reinforcement Learning

Aiming at the rapid growth of network services,which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain(SFC)under 5G networks,this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment(MADDPG-SD).Initially,an optimization model is devised to enhance the request acceptance rate,minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case.Subsequently,we model the dynamic problem as a Markov decision process(MDP),facilitating adaptation to the evolving states of network resources.Finally,by allocating SFCs to different agents and adopting a collaborative deployment strategy,each agent aims to maximize the request acceptance rate or minimize latency and costs.These agents learn strategies from historical data of virtual network functions in SFCs to guide server node selection,and achieve approximately optimal SFC deployment strategies through a cooperative framework of centralized training and distributed execution.Experimental simulation results indicate that the proposed method,while simultaneously meeting performance requirements and resource capacity constraints,has effectively increased the acceptance rate of requests compared to the comparative algorithms,reducing the end-to-end latency by 4.942%and the deployment cost by 8.045%.

Optimization and Characterization of Combined Degumming Process of Typha angustata L. Stem Fibers

Plant derived natural fibers have been widely investigated as alternatives to synthetic fibers in reinforcing polymers.Researchers over the years have explored many plant fibers using different extraction processes to study their physical,chemical,and mechanical properties.In this context,the present study relates to the extraction,characterization,and optimization of Typha angustata L.stem fibers.For this purpose,desirability functions and response surface methodology were applied to simultaneously optimize the diameter(D),linear density(LD);yield(Y),lignin fraction(L),and tenacity(T)of Typha stem fibers.Typha stems have been subjected to both alkali(NaOH)and enzymatic(pectinex ultra-SPL)treatments.Three levels of process variables including enzyme concentration(10,15,and 20 ml/L)and treatment duration(10,15,and 20 days)were used to design the experiments according to the factorial design.Experimental results were examined by analysis of variance and fitted to second order polynomial model using multiple regression analysis.The Derringer’s desirability function released that the values of process variables generating optimized diameter,linear density,yield,lignin ratio and tenacity are 20 ml/L and 20 days for concentration of pectinex ultra-SPL enzyme and treatment duration,respectively.Confirmation was performed and high degree of correlation was found between the experimental and statistical values.Moreover,the morphological structure has been investigated by the scanning electron microscope,showing a crenelated structure of ultimate fiber bundles of cellulose composing the Typha fiber.Compared to Typha stem non-treated fibers(TSNTF),Typha stem combined treated fibers(TSCTF),brings to improve mechanical properties.This change in mechanical properties is affected by modifying the fiber structure showing alpha cellulose of(66.86%)and lignin ratio of(10.83%)with a crystallinity index of(58.47%).

Processing Treatments of Beniseed (<i>Sesamum indicum</i>Linn) on Nutrients, Anti-Nutrients Composition and Functional Properties of Flour

Beniseed is an important oilseed, with high oil content and nutrient composition. The effect of processing (roasting, soaking, boiling, and germination) on proximate, mineral composition, anti-nutrients and functional properties of the beniseed flour were analysed. Also the sensory properties of cookies from blends of wheat and beniseed flours were determined. The results showed that moisture, fat, crude protein, carbohydrate, ash and crude fibre contents of the flours were significantly different and ranged from 3.20% - 4.79%, 34.34% - 50.43%, 15.19% - 30.65%, 18.90% - 22.16%, 4.54% - 6.01% and 4.30% - 7.59%, respectively. Processing significantly (p < 0.05) reduced the anti-nutritional factors and germination gave the highest mineral values in the beniseed flours. Water absorption capacity, oil absorption capacity, foaming stability, foaming capacity and swelling index, ranged from 1.00 - 1.28, 1.10 - 1.13, 98.72 - 108.82, 2.94 - 19.80 and 1.14 - 1.54 respectively. Sensory evaluation showed that 20% soaked beniseed flour substitution of wheat had no significant difference with 100% wheat cookies. Germinated sample gave a more desired nutrient composition (low fat and carbohydrate, high protein and mineral composition) but performed poorly in sensory attributes. In conclusion, beniseed gave a good flour blend with wheat in baked products, also further processing of the germinated flour to improve the appearance will give more nutritious cookies.

Weyl Group Orbit Functions in Image Processing

We deal with the Fourier-like analysis of functions on discrete grids in two-dimensional simplexes using C- and E-Weyl group orbit functions. For these cases, we present the convolution theorem. We provide an example of application of image processing using the C-functions and the convolutions for spatial filtering of the treated image.

A design and application of compound multi-functional sensor in wood-based panel processing

A compound multi-functional sensor was designed by the study on the on-line testing technology of wood-based panels, and its properties of shape, functions, size, resistance to special environment were studied in details. The operational principles of different sensors, technical flow of manufacturing, development of software systems of special functions, and the assessments of technical specification were also be introduced. This sensor adopted many new technologies, such as the applications of piezoresistant effect and heat sensitive effect can effectively measure the pressure and temperature, digital signal processing technology was used to extract and treat signals, and resist interference, encapsulation technology was used to keep the normal run of sensor under a harsh environment. Thus, the on-line compound multi-functional temperature/pressure sensor can be applied better to supervise the production of wood-based panels. All technical specifications of the compound multi-functional sensor were tested and the results met the requirements of the equipments.

ON THE RUIN FUNCTIONS FOR A CORRELATED AGGREGATE CLAIMS MODEL WITH POISSON AND ERLANG RISK PROCESSES

This article considers a risk model as in Yuen et al. （2002）. Under this model the two claim number processes are correlated. Claim occurrence of both classes relate to Poisson and Erlang processes. The formulae is derived for the distribution of the surplus immediately before ruin, for the distribution of the surplus immediately after ruin and the joint distribution of the surplus immediately before and after ruin. The asymptotic property of these ruin functions is also investigated.

Markov process functionals in finance and insurance

The Markov property of Markov process functionals which are frequently used in economy, finance, engineering and statistic analysis is studied. The conditions to judge Markov property of some important Markov process functionals are presented, the following conclusions are obtained： the multidimensional process with independent increments is a multidimensional Markov process; the functional in the form of path integral of process with independent increments is a Markov process; the surplus process with the doubly stochastic Poisson process is a vector Markov process. The conditions for linear transformation of vector Markov process being still a Markov process are given.