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In the quantitative analysis of spectral data, small sample size and high dimensionality of spectral variables often lead to poor accuracy of a calibration model. We proposed two methods, namely sample consensus and unsupervised variable consensus models, in order to solve the problem of poor accuracy. Three public near-infrared (NIR) or infrared (IR) spectroscopy data from corn, wine, and soil were used to build the partial least squares regression (PLSR) model. Then, Monte Carlo sampling and unsupervised variable clustering methods of a self-organizing map were coupled with the consensus modeling strategy to establish the multiple sub-models. Finally, sample consensus and unsupervised variable consensus models were obtained by assigning the weights to each PLSR sub-model. The calculated results show that both sample consensus and unsupervised variable consensus models can significantly improve the accuracy of the calibration model compared to the single PLSR model. The effectiveness of these two methods points out a new approach to achieve a further accurate result, which can take full advantage of the sample information and valid variable information.

One of the major restrictions in spectroscopic analysis is the limited number of calibrations, especially for biological samples. Meanwhile, there is a lack of effective algorithms to simulate synthetic spectra from the real spectra of limited samples. Thus in this work, a boundary equilibrium generative adversarial network (BEGAN) was proposed to automatically generate synthetic spectra and successfully produce spectra from two datasets. Then, the impact of the diversity ratio was estimated in the aspect of the quality and diversity of the generated spectra by BEGAN, and a negative correlation was found between quality and diversity. Finally, these synthetic spectra are applied in a consensus algorithm named creating diversity partial least squares (CDPLS) to replenish virtual samples in every iteration. Results show that the synthetic spectra generated by BEGAN are of high quality and improve the predictive performance of CDPLS. It can concluded that BEGAN has the potential to generate derived homologous spectra and expand the number of spectra in some small sample sets.

The advantage of data-sensitive deep learning methods used in spectral calibration is not obvious when the amount of available data is insufficient. To solve this problem, this paper proposes a new method that combines one-dimensional convolution neural network (1-dim CNN) with negative correlation learning (NCL). First, we create several identical one-dimensional convolutional neural networks as subnetworks of the NCL system. Second, we add the error function of each subnetwork to a negative correlation penalty term that is related to the correlation between the networks and then use this composite error function to back-propagate these networks for parameter adjustment. Finally, after the model has converged, we take the average of the results of all subnetworks as the result of the whole model. We compare CNN_NCL with PLS,creating diversity partial least squares (CDPLS) and a single 1-dim CNN on the pharmaceutical tablet dataset and diesel fuels dataset. The experimental results show that CNN_NCL performs better than PLS and CDPLS when the number of samples is sufficient. Additionally, CNN_NCL can always be more effective than a single CNN regardless of the data scale. Therefore, in the context of the era of big data, CNN_NCL is a fairly efficient model for spectral calibration.

Cloud storage is a service provided by cloud service provider (CSP). More and more individuals and organizations accept the scheme and outsource their data to CSP seeking to reduce local storage burden. Since the outsourced files are no longer under the data owners' direct control and CSP is not trustworthy, it is necessary for data owners to check the integrity of their files outsourced to CSP. To address this crucial problem, some provable data possession (PDP) protocols have been presented. In order to obtain higher availability, storing multiple replicas is a common strategy in cloud storage. Most recent researches on multiple-replica provable data possession (MR-PDP) use homomorphic linear authenticators (HLAs) to generate aggregated tags for the blocks at the same indices in each replica, but it cannot verify single replica to identify the corrupted replicas. In this paper, we proposed a novel multiple replica provable data possession scheme, named FMR-PDP. In FMR-PDP, we compute tags based on vector dot product instead of expensive group exponentiation operations, and only generate one tag for all blocks at the same indices in each replica. Our FMR-PDP scheme supports a flexible data possession verification, which means the data owner can check any number of replicas in a verification. In addition, we make a comprehensive performance analysis, which shows that our proposed scheme is flexible and efficient.

In order to improve the accuracy of tracking the path and control the car velocity accurately on the hillside. The optimized fuzzy-PID control strategy is put forward and designed. On the platform of ATMEGA2560 microcontroller, the position of the car is adjusted by using the altitude algorithm constantly, and the optimal path strategy is carried out according to the optimized fuzzy-PID control algorithm, the velocity of the car is controlled at the same time. The algorithm has been tested again and again to modify the parameters, and achieves a good effect of tracking and planing the desired path.

This study introduces a spectral-recognition method based on sparse representation. The proposed method, the linear regression sparse classification (LRSC) algorithm, uses different classes of training samples to linearly represent the prediction samples and to further classify them according to residuals in a linear regression model. Two kinds of spectral data with completely different physical properties were used in this study. These included infrared spectral data and laser-induced breakdown spectral (LIBS) data for Tegillarca granosa samples polluted by heavy metals. LRSC algorithm was employed to recognize the two classes of data, and the results were compared with common spectral-recognition algorithms, such as partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), artificial neural network (ANN), random forest (RF), and support vector machine (SVM), in terms of recognition rate and parameter stability. The results show that LRSC algorithm is not only simple and convenient, but it also has a high recognition rate.

Products, place, price and promotion strategies of fresh blueberries are tried using marketing strategy theory in this paper. The results showed that marketing strategies are established according to different consumer groups. At present, product strategy is used to be the high-level. Over-head price is the best price strategy. Plastic boxes containing 125 g fresh blueberries are common for package strategy. Supermarket is the chief terminal market for fresh blueberries.

The platform of distributed design and resource sharing is important for medium-sized and small companies in developing products to improve competitiveness. As a background of creative product design, a knowledge model based on product collaborative innovation development of products (CIDP) is proposed. Characteristics of CIDP are analyzed, and the framework and key technologies of the CDDP-platform based knowledge studied. Through integration of existing system and interface designs, a development platform has been built to support the PCID within knowledge-based engineering (KBE). An example is presented, indicating that the prototype system is maneuverable and practical.

Wireless local network (WLAN) is developing to a ubiquitous technique in our daily life recently. As a related product, WLAN based indoor positioning system is getting more and more attention. Fingerprint is a mainstream method of wireless indoor positioning, but it has the shortcomings of that received signal strength (RSS) is multi-modal and sensitive to environmental factors. These characters would adversely affect the performance of positioning system. To address this issue, a filtering algorithm based on multi-cluster-center is proposed in this paper. We use this algorithm to optimize the training samples at off-line phase to improve the performance of nonlinear fitting with the fingerprint feature, and further enhance the positioning accuracy. Finally, the positioning accuracy before and after filtering is compared with multiple sets of real RSS samples. The simulation results show that it is a reliable algorithm to enhance the performance of WLAN indoor positioning.

Calculates the envelope thermal characteristics of the Phase Change Material (PCM) lightweight building fabrics, such as the thermal inertia index, storage heat coefficient, delay time and attenuation ratio,ect. Comparing with the common lightweight building fabric the envelope thermal characteristics of the PCM lightweight building fabrics has been improved preferably. The thermal inertia index, attenuation ratio and delay time of PCM components are respectively the 3.75,14 and 10 times as the one of the common building fabrics. So, it will be less cooling load in the PCM lightweight building than the common lightweight building. Then combining the nighttime ventilation we carries through the contrast experiments between light weight PCM wall and ordinary building in chongqing summer, the results show that the electricity consumption in light weight PCM wall room be 32.5% less than the one in ordinary room, the results also show that outdoor temperature have great effect on the energy efficiency.

Constructing metro tunnel in shallow stratum destroys surrounding stratum structure, causing corresponding deformation and settlement of stratum. So it’s very important to accurately predict stratum deformation and settlement for metro tunneling. In this paper, the features of FLAC3D and built-in material constitutive model are firstly analyzed, then compared with other calculating procedures, besides it is used to predict stratum deformation and settlement caused by the Shenzhen metro tunneling. It can be seen from the numerical results of the calculation obtained from FLAC3D that stratum deformation and settlement agree well with that of in-situ measurement, and can reflect the typical characteristics and change laws of stratum deformation and settlement caused by metro tunneling, which indicates that using FLAC3D to analyze stratum deformation and settlement caused by metro tunneling is feasible.

A measurement experience for the downlink channel of the low earth orbit (LEO) satellites at UHF band was carried out by utilizing a dedicated simulator which could totally simulate an in-orbit LEO satellite. Results including the spectrum of the received signal, the multipath delay over the chip period, the sub-chip multipath delay and the Ricean K-factor were presented for a wide range of propagation surroundings, such as urban, suburban, open environments. The results can be utilized to optimize the design of the LEO mobile satellite systems, especially the Rake-receiving strategy and the dynamic property of the receiver.

Due to the special geological conditions and the surrounding environmental conditions, the urban metro constructions are faced with greater technical difficulty and higher safety risk, which cause many kinds of safety accidents. Taking Beijing metro as the background, the characteristics of the metro project and the main safety risks have been analyzed, and a statistical analysis of accident cases caused by Beijing metro construction has also been made. According to the inducements, the accidents will be divided into 5 categories: accidents caused by pipeline leakage or rupture, bad geology-induced accidents, overmuch deformation of strata-induced accidents, management defects and unexpected accidents, of which management defects are the biggest contributor, and the most serious accidents are caused by pipeline leakage or rupture and bad geology. At last, combined with typical cases, the characteristics and dangers of accidents caused by pipeline rupture and unfavorable geology are analyzed. In addition, countermeasures to prevent and control accidents are proposed.

A method used to analyze the two-dimension or three dimension slope stability is presented in this paper. According to the stress analysis results of elastic-plastic finite element method, the method makes sure of potential slip surfaces, the most dangerous surfaces and stability safety factor of slope by means of numerical integration, and the method has rigor theoretical basis. Through many examples and engineering tests, it shows that slope stability safety factor and the most dangerous surface using general way are quite different from real fact, and that the proposed method is proved correct.

A new kind of oil-mist collection is design to reduce the harm of oil-mist produced by cold-former to people and environment. This paper stimulates the flow field of oil-mist cooling and separation device by using Fluent and obtains the speed vector by adopting the standard κ -ɛ turbulence model and supplying air from different speed. It is validated that the device is a perfect part of the oil-mist collection. (5 pages)

Modelling technology of bone repair bionic scaffold plays a key role in the process of repairing defective bone based on tissue engineering. In this paper, through studying the structure of bone repair bionic scaffold, a new method of constructing the CAD model of bone repair bionic scaffold based on tissue engineering is put forward :Via programming, bone medical images are processed; Then external shape of scaffold and negative of pore structure are constructed; Finally, Boolean operation proceeds between external shape of scaffold and negative of pore structure to get the three- dimensional digital model of bone repair bionic scaffold. Via the system implemented by this method, favourable model of bone repair bionic scaffold for repairing a skull is obtained. On the other hand, the problem of diminishment of pore aperture and internal of bone repair bionic scaffold is also discussed and solved. Data structure and forming method of digital model are also presented in this paper. The method presented in this paper to construct the model of bone repair bionic scaffold is easy to be operated and can produce good effects, which is more suitable to implement the industrialization of repairing bone defects based on tissue engineering than conventional CAD methods.