Intelligent Decision Support Algorithm Based on Self-Adaption Reasoning

This paper analyzes the logic deduction and reasoning techniques used in several intelligent decision support algorithms, and proposes a flexible planning method GARIv using fuzzy descriptive logic in media enterprise management. Combined with experiments, the above methods are illustrated in terms of effectiveness and feasibility. In the end, the challenges and possible solutions of intelligent decision support algorithms with self-adaption reasoning are discussed

Comprehensive Analysis of the Relationship Between RAS and RAF Mutations and MSI Status of Colorectal Cancer in Northeastern China

Background/Aims: Colorectal cancer (CRC) is mainly caused by chromosomal instability (CIN) and microsatellite instability (MSI). The RAS and RAF genes are essential components of the CIN pathway, and several studies have found that RAS and RAF mutations are associated with MSI status in CRC. Here, we examined these three factors in CRC in Northeast China and aimed to reveal new details of the relationship between these mutations and MSI status. Methods: This study involved 290 patients with CRC who had RAS or RAF gene mutation detected using fluorescence-based allele-specific polymerase chain reaction or Sanger sequencing. The majority of the identified patients were found to harbor MSI (MSI status). Accurate molecular detection was carried out using formalin-fixed paraffin-embedded tissue or blood samples. Results: The rates of RAS and RAF mutations were 58.5% and 4.1%, respectively. The prevalence of RAS mutation in CRC was clearly higher and that of RAF mutation was lower in Northeast China compared with previously reported cohorts in other locations. High MSI level (MSI-H status) was more complex, at around 10%. This was consistent with previous data from China. However, compared with data reported from other continents, MSI-H was higher than that of Japan or South Korea in Asia, and lower than that of Europe or the United States. Conclusion: RAS/RAF mutations and MSI status in CRC are closely associated with tumor location and ethnicity. Further studies investigating the relationship between these three factors can help in the development of treatment strategies for patients with CRC

Research on an online self-organizing radial basis function neural network

A new growing and pruning algorithm is proposed for radial basis function (RBF) neural network structure design in this paper, which is named as self-organizing RBF (SORBF). The structure of the RBF neural network is introduced in this paper first, and then the growing and pruning algorithm is used to design the structure of the RBF neural network automatically. The growing and pruning approach is based on the radius of the receptive field of the RBF nodes. Meanwhile, the parameters adjusting algorithms are proposed for the whole RBF neural network. The performance of the proposed method is evaluated through functions approximation and dynamic system identification. Then, the method is used to capture the biochemical oxygen demand (BOD) concentration in a wastewater treatment system. Experimental results show that the proposed method is efficient for network structure optimization, and it achieves better performance than some of the existing algorithms

Fragility Analysis of Step-Terrace Frame-Energy Dissipating Rocking Wall Structure in Mountain Cities

Rocking walls can control the overall deformation pattern and the distribution of plastic energy dissipation in structures, suppressing the occurrence of weak layers. In the case of step-terrace frame structures, issues such as severe lateral stiffness irregularities, abrupt changes in floor-bearing capacity, and concentrated deformation in upper ground layers exist. To improve the yielding and failure modes of step-terrace frame structures in mountainous regions, this paper proposes a structural system combining step-terrace frame structures with energy dissipation rocking walls attached to their bottoms, aiming to control the yielding mechanism of the structure, further reduce the seismic response, limit residual deformation, and propose a structural system of step-terrace frame structures with buckling-restrained braces (BRBs) and energy dissipation rocking walls. Two sets of numerical models for step-terrace frame structures with different numbers of dropped layers and spans were established. Through simulating low-cycle repeated loading tests on step-terrace frame structures, the rationality of the models and parameters was verified. Incremental dynamic analysis (IDA) was employed to systematically investigate the vulnerability of step-terrace frame structures with energy dissipation rocking walls under different dropped layer and span configurations. This investigation covered aspects such as IDA curve clusters, percentile curves, seismic demand models, fragility functions, failure state probabilities, vulnerability indices, collapse resistance factors, and safety margins. The results indicated that the change in dropped layer numbers had a far greater impact on the vulnerability of step-terrace frame structures with energy dissipation rocking walls than the change in dropped span numbers. Under seismic excitations with the same peak ground acceleration (PGA), rocking walls can limit the depth of structural plasticity development, reduce the dispersion of peak responses, and lower the probability of exceeding various performance levels, thereby exhibiting good collapse resistance. The addition of buckling-restrained braces (BRBs) can further enhance the seismic performance and collapse resistance of the rocking wall frame structure. By analyzing the correlation between seismic intensity measures and peak structural responses, the validity of using peak ground acceleration as a scaling indicator for incremental dynamic analysis (IDA) has been verified

An innovative course about network storage and system virtualization technologies in PKU

Network Storage and System Virtualization Technologies is an up-to-date course opened by the school of electronics engineering and computer science of Peking University. The purpose of this course is to help students to catch up with the fast development of computer science. The theory and the practice of the course mainly give emphasis on the design of data center , including network storage and system virtualization . In addition, this course sets up experiments related with virtualization, combining multicore technology and network storage technology. © 2010 IEEE

Study on Design of Magnetic Flux Leakage Testing Instrument for gun

Abstract: The paper describes the magnetic Dipole model of magnetic flux leakage(MFL) based on the principle of MFL testing, proposes the effects of surface defect width and depth on MFL field, and presents the peak-peak amplitude algorithm that the features of defect signal are extracted. The peak-peak amplitude and separation, signal gradient variation are used as the distinguish criterions of defects. The principle of instrumental hardware design is also introduced. The introduced gun MFL testing instrument is successfully employed in the nondestructive evaluation of gun. Keyword: magnetic flux leakage; defect; nondestructive evaluation; peak-peak amplitude algorithm; hardware design CLC number: TG115.28;TJ306 Document code: A Article serial number:1008-0570 The parts of gun often create crack when used for a period, in order to avoid accident caused by crack, we must detect it periodically, this is very important for the safely operation and the safety of the operator. The magnetic flux leakage(MFL) detecting method is very sensitive to the crack on ferromagnetic materials, and with low cost and simple arts and crafts. So it is very widely used in the crack detection for gun. The principle of MFL non-destruction is as follows. The gun's parts is first magnetized by a magnetizer containing high-strength Nd-Fe-B(Neodymium-Iron-Boron) permanent magnets, then if there is crack on the surface of gun part, the magnetic conductance of the position with crack will be lower than usual, the magnetic resistance will be higher, and the magnetic line will be focused below the crack and magnetic field will leak out of the ferromagnetic material, then we can detect the leakage magnetic field and find the crack. With different kinds of shape of the cracks or different kinds of size, the leakage field will be different. The leakage field can be detected by Hall-effect sensor, and we can estimate the size of the crack by the leakage field gained by Hall sensor. And so we can implement the non-destructive detection for the gun. 1 The model of MFL for crack The distribution of leakage magnetic field varied with different kinds of the geometric shape of the crack, we can know from information that by statistical almost all of the shape of crack are V-shape, so we adopt the V-shape crack model to study the leakage field and try to find the connection between the crack size to leakage magnetic field. It is non-linearity for the magnetization of the parts of the gun's material, so, in order to simplif