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Brain source localization from electroencephalogram (EEG) signals is an challenging problem for noninvasively localizing the brain activity. Conventional methods use handcrafted regularization terms based on neural-physiological assumptions by exploiting the spatial-temporal structure on the source signals. In recent years, deep learning frameworks have demonstrated superior performance for solving the inverse problems in the natural and medical imaging field. This study proposes a novel unsupervised learning training-free framework based on Generative Adversarial Networks and deep image prior (GANs-DIP) as a generative model simulating spatially structured source signal. The proposed framework can faithfully recover extended source patches activation patterns of the brain in an unsupervised manner. Numerical experiments on a realistic brain model are performed under different levels of signal-to-noise ratio (SNR). The proposed model shows satisfactory performance in recovering the underlying source activation.

Colorectal cancer is a heterogeneous disease. Its response to targeted therapies is associated with various factors, and the treatment effect differ significantly between individuals. Personalize medical treatment (PMT), which takes into consideration of individual patient characteristics, is the most effective way to deal with this issue. Patient similarity and clustering analysis is an important part in PMT. Earlier works mainly focused on similarity computation among the patients but overlook to preserve relationships. This paper presents a formal concept analysis-based approach for computing the similarity between colorectal cancer patients. The approach not only does the clustering of patients based on their similarity but also can preserve the relations between clusters in hierarchical structural form. This would allow us to build a knowledge base which is helpful for clinicians to take fast and effective decision for treatment and care of colorectal cancer patient.

A triple-band bandpass filter (BPF) using stub loaded quarter-wavelength triple-mode resonators is presented in this letter. Based on the resonance characteristics analysis, it is found that the fundamental mode and the third harmonic in the quarter-wavelength resonator can be independently controlled by the length of quarter-wavelength resonator and the length of short-circuited stub. Furthermore, a new mode is achieved by a novel technique of loading an open-circuited stub on a short-circuited stub. Finally, triple-band BPF is designed, fabricated, and measured to verify the design principle. Good agreement is achieved between the theoretical, simulated and measured results.

Software defect prediction is very important in software engineering. It uses the defects found in historical software modules to predict defects in new software modules, and provides decision support for planning and process management in software project. Machine learning is one of the core research directions in the field of artificial intelligence and covers many disciplines. In the research of software defect prediction, various machine learning methods have been widely studied and applied, and have been verified to obtain good performance. In this paper, the basic framework of software defect prediction model based on machine learning is described, several important prediction models are studied and discussed. Finally, the main problems of software defect prediction are summarized, and corresponding solutions are proposed.

Magnetoencephalography(MEG) is a functional, noninvasive technology for recording neuronal activity of human brain in real-time. MEG has been approved as an efficient and powerful functional detection method which has been used in clinical practices relate with epilepsy, depression, and other diseases that cannot be well-diagnosed by traditional structural methods, e.g., CT and MRI. By using MEG, very weak magnetic signals typically in the range of 10 femtotesla (fT)-1 picotesla (pT) that originate from electric currents flowing in neurons, can be recorded. Compared with scalp EEG, MEG provides much better spatial resolution. Meanwhile, MEG is a noninvasive technology for preoperative workup for epilepsy surgery, which means it may replace traditional invasive methods. As the development of high-sampling rate MEG systems as well as the discovery high-frequency oscillations (HFOs) in the brain, MEG is now typically digitally analyzed in very high-frequency range. Although MEG has been clinically used for two decades, it is not so widely-used as EEG. The lack of a powerful software platform is an important reason which hinders the development of MEG. A MEG-specific software, MEG processor, was released here. With the friendly graphical user interface (GUI) of MEG Processor, researcher can easily identify/mark HFOs and project the signal to MRI receiving a precise 3D reconstruction. We hope such a platform will help and encourage more clinicians to uncover the magnificent features of MEG.

This paper presents a novel modified coaxial cavity resonator and its application to bandpass filters (BPF) with compact size. Unlike the conventional coaxial cavity resonator, the proposed resonator is made up of multi-metal-slices-loaded on the inner coaxial conductor within a single rectangle cavity. The technique with multi-metal-slices is applied to enhance the self-inductance and self-capacitance of the coaxial cavity resonator which leads to size reduction. Based on the research of position and size for the loading multi-metal-slices, an efficient way to load is proposed, Compared to the conventional coaxial cavity resonator, the central frequency can be reduced. Finally, a simulation example of BPF using this technique is presented to validate this attractive design concept.

The main purpose of our research is to apply the Arduino platform to design an anti-theft system that incorporates GPS satellite positioning, and use sensors to control peripheral devices in the car to reduce the risk of car theft. The anti-theft tracking allows the user's mobile phone to locate the current position of the car on the Google map immediately, and the reed switch on the door device to determine whether there is an improper external force to open the door, and the anti-theft system activates the front windshield to be completely black.

With the economy globalization, the transnational power grid interconnection projects will inevitably become an important direction of investment in power grid, in order to evaluate the comprehensive benefits of such investments in the round and improve the accuracy of investment decisions, a comprehensive benefit evaluation index system suitable for such projects is constructed. In order to make full use of the subjective and objective information, this paper uses the combination weight method of analytic network process and artificial bee colony algorithm to determine index weight, and makes the comprehensive benefit evaluation of such projects by improved matter-element extension model. The research can provide a decision reference for the investment of transnational power grid interconnection projects.

Supply chain contract is becoming an academic and business circles' hot topic. This paper built a two-echelon supply chain structure model with the quantity flexibility supply contract, and then simulated this model. The research indicated that the complex relation among factors of quantity flexibility supply contract could be better revealed with the use of system dynamics methodology. Finally, under the conditions in this paper, an optimal set of parameters that can coordinate the supply chain would be given to the retailer.

In this study, a backstepping fuzzy-neural-network control (BFNNC) is designed for the on-line levitated balancing and propulsive positioning of a hybrid magnetic-levitation (maglev) transportation system. In the proposed BFNNC scheme, a fuzzy neural network (FNN) control is utilized to be the major control role by imitating a backstepping control (BSC) strategy, and adaptation laws for network parameters are derived in the sense of projection algorithm and Lyapunov stability theorem to ensure the network convergence as well as stable control performance. The effectiveness of the proposed control strategy for the hybrid maglev transportation system is verified by experimental results, and the superiority of the BFNNC scheme is indicated in comparison with the BSC strategy and the backstepping particle-swarm-optimization control (BSPSOC) system in previous research.

At present RFID indoor positioning data visualization methods are simple and the visual effect is not ideal. To solve this problem, a method is put forward, which can make RFID indoor localization algorithms implement in a geographic information system. By overlaying the CAD floor plan with the outdoor maps, every indoor space positioning result has a unique geographic coordinate. To combine RFID indoor positioning technology with the real geographic environment information, the calculating coordinates are visualizing displayed by using the geographic information system. Real-time targets positioning and the visualization display of RFID indoor positioning data are realized through building the RFID indoor positioning system which is based on spatial geographic coordinates. System test results indicate that this technology can achieve ideal indoor positioning data visualization effect under well indoor positioning precision.

The reliability and robustness of a safety-related system can be ensured by using international standards, such as ISO 26262, to develop and verify the functional safety of the system. This research proposes a safety validation and risk reduction (SVRR) process based on ISO 26262 safety standards for decreasing risk and validating safety in model-based design platform. The proposed safety process can be employed to identify the crucial components in the system, and the effects of such crucial components' failures on the functional safety can be effectively mitigated through fault-tolerant mechanism protection. An emergency brake control algorithm and brake-by-wire system was developed through the SVRR process built in NI and dSPACE system design platform. Simulation-based fault injection campaigns were performed and the experimental results show the degree of severity of the components' failures to the system and the robustness of the system. We then employ a fault-tolerant mechanism to protect the most vulnerable component to improve the system safety.

A directional constant beamwidth (DCB) beamforming algorithm is introduced, which keeps the beamwidth unchanged when the mainlobe is steered to a large range of angles. The algorithm is based on the optimization theory that minimizing the sidelobe level subjects to the minimum mean square error between the designed mainlobe under all directions and the corresponding reference mainlobe. The introduced algorithm can be written in the form of second order cone programming (SOCP) and can be solved by some certain matlab toolboxes. It is shown by simulation that the new algorithm can form the directional constant beamwidth beampattern effectively under the designed mainlobe direction from -60° to +60°.

A method for maximize profit of greenhouse temperature control was proposed. Take lettuce planting as an example, a non-linear model was set up for forecasting plant growth rate by neural network, and a market price model was established for forecasting plant market price by Polynomial fitting function. In terms of the above two models and the cost of temperature adjustment based on energy balance, the optimal set-point of temperature would be found out. With the actual situation and the establishment of three models, a multi-information fusion was achieved, which provided a theory for the decision-making of greenhouse temperature control system.

With the development of 3G network technology, the rapid upgrading of mobile phone hardware, and the refined requirements for mobile phones by mobile phone users, it is essential for mobile phones to be able to promptly and accurately process images. A mobile phone terminal sends the service requests to cloud computer system which then processes the requests and sends the results via 3G network back to the mobile phone terminal. This paper presents a architectural model to realize the image processing system that connects mobile phone with clouding computing through 3G network. The method is to build intra-enterprise server group, distributed database system, and parallel computing system to form a private cloud computing system, which defines ontological semantic tags for images uploaded from mobile phone terminals and stores them in a distributed way (cloud storing), and to design the corresponding search algorithms to help the system to promptly and accurately query the images (cloud computing), and retrieve the appropriate images through sorting matching indexes, weights, and etc.

Modern teaching theory is presented in this paper and the discovery learning strategy is introduced into Surveying education. The concept of discovery learning is firstly discussed, and then the paper point out that the discovery learning is the inherent needs of the content of surveying. The teaching mode of Surveying based on discovery learning theory is proposed and analyzed with respect to specific teaching contents. At last, teaching and learning strategy is studied in four aspects: the strategy of question, the strategy of situation, the strategy of information and the strategy of homework.

This paper presented a novel application of Magneto encephalography (MEG) and diffusion tensor image (DTI) on word recognition, in which the spatiotemporal signature and the neural network of brain activation associated with word recognition were investigated. The word stimuli consisted of matched and mismatched words, which were visually and acoustically presented simultaneously. Twenty participants were recruited to distinguish and gave different reactions to these two types of stimuli. The neural activations caused by their reactions were recorded by MEG system and 3T magnetic DTI scanner. Virtual sensor technique and wavelet beam former source analysis, which were state-of-the-art methods, were used to study the MEG and DTI data. Three responses were evoked in the MEG waveform and M160 was identified in the left temporal-occipital junction. All the results coincided with the previous studies’ conclusions, which indicated that the integration of virtual sensor and wavelet beam former were effective techniques in analyzing the MEG and DTI data.

The images, in high-throughput genome sequencing of sequencing by synthesize, consist of A, C, G, T base fluorescence images, and the fluorophore emission spectra partially overlap, which causes cross-talk problem. This paper presents a method of correlation analysis, construct the calibration matrix to eliminate interference of the fluorophore. The experiment result shows the method provided in this article is effective to correct cross-talk influence, and get the deconvolution of the clusters signal.

Recent studies have found the consistent contralateral high gamma activities in sensorimotor cortex in adults during a unilateral finger movement. However, no study has ever reported the same phenomenon in children. We hypothesized that the contralateral high gamma activities also exist in children during a unilateral finger movement. Sixty normal children (6-17 years old) were studied with a 275-channel MEG system combined with synthetic aperture magnetometry (SAM). Sixty participants displayed consistently contralateral event-related synchronization (C-ERS) within high gamma band (65-150Hz) in primary motor cortex (M1) of both hemispheres. Interestingly, nineteen younger children displayed ipsilateral event-related synchronization (I-ERS) within the high gamma band (65-150Hz) just during their left finger movement. Both I-ERS and C-ERS were localized in M1. The incidence of I-ERS showed a significant decrease with age. Males had significantly higher odds of having ipsilateral activity compared to females. Noteworthy, high gamma C-ERS appeared consistently, while high gamma I-ERS changed with age. The asymmetrical patterns of neuromagnetic activities in the children's brain might represent the maturational lateralization and/or specialization of motor function. In conclusion, the present results have demonstrated that contralateral high-gamma neuromagnetic activities are the potential biomarkers for the accurate localization of the primary motor cortex in children. In addition, the interesting finding of the ipsilateral high-gamma neuromagnetic activities open a new window for us to understand the development changes of the hemispherical functional lateralization in the motor system.

The aqueous removal of sulfur dioxide (SO 2 ) by oxidation of Mn 2+ catalytic ozone was investigated in the experiments, so as to find the effects of Mn 2+ for aqueous removal of SO 2 by ozone. The concentration curve of ozone was measured by standard iodine measurement method. The operating factors included mole ratio of ozone to SO 2 and the concentrations of Mn 2+ . When absorption solution has no Mn 2+ , the removal efficiency of SO 2 is 35% at 0.5 mole ratio of O 3 to SO 2 , but the efficiency is 70% when Mn 2+ is put into absorption solution at the same mole ratio of O 3 to SO 2 . As it is increasing, the removal efficiency of SO 2 increases. And as concentration of Mn 2+ increases, the efficiency also increases. At the end of the experimental studies, we made the conclusion that the optimal concentration range of Mn 2+ for the aqueous removal of SO 2 by Mn2+ catalytic ozone is 1.2A—10 -2 ~1.2A—10 -1 mol/L.

Under the background of global economic crisis, more and more local governments regard city marketing as a significant mode for urban development so as to strengthen urban competitiveness for more external development resources. However, since the social economic system of China is currently in a transitional period, decentralization, marketization and globalization urge the local governments to bear a strong developing impulse and marketing characteristics, which makes city marketing in China demonstrate a distinct business orientation and consequently causes many disadvantageous effects on the health and stability of urban development in China. Therefore, this paper focuses on the innovation of urban governance mechanism and, based on a comparative analysis of two urban development modes in transition in China, i.e. marketing type and endogenous type, puts forth the main characteristics and constructs theoretical frame of endogenous urban development mode.

With the transformation of China's economy and social development, the issue of spatial expansion of the urban construction land and its driving forces has drawn extensive attention from both academic researchers and government departments. The analysis from the perspective of mega-events driving forces is firstly adopted in this paper, to take Taizhou metropolitan area in Jiangsu Province as a case study, which is a representative in the Yangtze River Delta in China's urbanization process. Remote sensing interpretation data of Landsat TM, and ALOS which represent main years' images of Taizhou metropolitan area within the last 20 years are used in the analysis. From the perspective of mega-events driving forces, statistical analysis, together with remote sensing, geographic information system methods and procedure analysis, is adopted to analyze the spatial expansion of urban construction land in Taizhou metropolitan area. The main conclusions are: the mega- events driving forces play an important role in spatial expansion of the urban construction land. In different periods the driving forces of spatial expansion of the urban construction land are significantly influenced by the national, regional and urban mega-events. For the last two decades, the dominant patterns of Taizhou metropolitan area urban construction land, in terms of spatial expansion, are spot-filling and extension, as well as transformation, point-axle corridor pattern, and satellite city pattern, which jointly form an net expansion pattern. The temporal expansion, however, is characterized by rotating development between the south and the north districts, and between urban districts, rural villages, and port regions along the Yangtze River. No research on such issue before was from the perspective of the mega-events driving forces, so this is the academic innovation in this paper. The expansion of city construction land and its driving force has drawn extensive attention from both academic researchers and government departments as Chinese state council focuses greatly on urban construction land management. The discussions of the management are required from theoretical researches and real applications. From an original perspective of mega-events driving forces, this paper takes Taizhou metropolitan area in Jiangsu Province as a case. Not only extracting methods and techniques of urban land-use information with serial high spatial resolution in the background of multi-source data fusion and integration are solved in the research, but also basic spatial information for further study of urban sustainable development in the Yangtze River Delta is provided, with the special period background of Jiangsu Province's great development along the Yangtze River and notable ambition of the modernization in eastern China. Taizhou metropolitan area is selected as the case in our study for the following two reasons: On the one hand, Taizhou metropolitan area, located in the Yangtze River Delta agglomeration, is in the progress of rapid urban construction land expansion; on the other hand, the typical characteristic of Chinese urban construction land expansion is presented in the case: point-axle corridor pattern and net pattern — the northern part of Taizhou metropolitan area shows spot-filling and extension pattern in low density filling; the middle and southern parts of that display point-axle corridor pattern, and satellite city pattern, which jointly form an expansion net pattern in high density filling. International scholars researched on this issue mainly from the perspective of geography and economics. Urban spatial expansion can be categorized into five types: infilling, outspreading, linear development, extension, and large-scale projects (Roberto,2002)

Digital surface model (DSM) can be acquired from airborne Lidar (light detection and ranging) directly. But for the production of digital elevation model (DEM) from the point cloud, the filtering of the point cloud should be carried out in order to remove points representing surface of non-ground objects. According to the deficiencies of slope based method and characteristics of Lidar data in urban area, a novel filtering algorithm for Lidar data that combining slope based method and region growing is presented in this paper. This method can improve precision and efficiency of filtering, and is very suitable for Lidar data of complex urban area. Experiment results show that the proposed method can remove objects in complex urban area effectively and rapidly.

Along with the rapid development of urbanization and industrialization in China, the vast rural areas in China, especially in developed regions, is confronted with new development bottleneck and confusion. Under such circumstance, universal attention has been paid to urban-rural integrated planning as an effective way to promote positive interaction between urban and rural areas as well as a new perspective to study rural spatial distribution in a new area in China. By analyzing the concept and connotation of urban-rural integrated planning in combination with the case study of Jiangning subdistrict in Nanjing, this paper carries out some useful exploration in current problems and contradictions in rural spatial development, methods and principles for distribution planning as well as innovation of relative supporting policies and systems in China.

Our integrated college campus information system based on service-oriented architecture (SOA) technology can provide object-oriented half integrated services (OOHIS). It can automatically select corresponding components from system component library in response to different service objectives to build a general-purpose major integration service. Via timely building of system component library, the object-oriented customized services of various colleges can form the different integration services for different customers, including college leadership, faculty, students, administrators, staff, and etc.. Through our developed interfaces and middleware, an old campus IT system can be divided into multiple function components that can be later called by the new system service modules. The system takes advantage of the wire and wireless network technology of IPV6 to realize the seamless integration between the normal office system and mobile office system. We also use XML and Web server technology to implement the system.

In this study we present a new method to denoting DNA sequences based on the distributions of "stop-codon" and "reverse complementation stop-codon"(R14). Using the theory of Shannon entropy, we ameliorate the measure of the Jensen- Shannon divergence and beta - KL divergence, And we compare experimentation obtained by our method with the previous results, Show that recognition efficiency based on the new measures beta - KL divergence with the vector R14 rise 86%, And more than that of by Bernaola's meathods presented 70%.

This paper aiming at the characteristic of the ASK signal in audio frequency track circuit without insulation presents a new algorithm to demodulate the ASK signal-the demodulation algorithm of ZFFT, designs a demodulation system on the basis of TMS320C32. The result of experimentation shows that the system can demodulate the ASK signal reliably. It accords with the requirement in locale.