提升聋生“内存”四法

聋生学习和运用所学语言文字来记叙事情、表达思想都存在一个共同的现象:说话缺乏中心,思想表达不清,作文无从下手。教师如何改善聋生现状,提高他们的语言表达能力,值得聋教育工作者进行探讨。笔者认为,应从提高聋生的语言积累入手,扩大聋生的阅读范围,丰富聋生的词汇量,加强聋生的语言实践,从根本上提升聋生的"内存"。

击破Windows内存故障

我们的系统能否运行得顺畅自如，很大程度上取决于电脑的内存。不过内存可以说是一台电脑中最容易出现故障的配件之一，在内存出现问题时，我们只有及时排除故障，扫清隐患，才能让爱机工作得更加稳定、可靠。

内存换时间,13.6秒破解Windows密码

计算机世界网消息:瑞士的研究人员于当地时间本周二发表了一篇论文,提出了一种快速破解由字母、数字组成的Windows密码的方法,将破解这类密码的平均时间由1分钟41秒减少到了13.6秒。

Database-oriented storage based on LMDB and linear octree for massive block model

Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, including ACID-compliant, concurrency support, data sharing, and efficient access. Each block model is organized by linear octree, stored in LMDB（lightning memory-mapped database）. Geological attribute can be queried at any point of 3D space by comparison algorithm of location code and conversion algorithm from address code of geometry space to location code of storage. The performance and robustness of querying geological attribute at 3D spatial region are enhanced greatly by the transformation from 3D to 2D and the method of 2D grid scanning to screen the inner and outer points. Experimental results showed that this method can access the massive data of block model, meeting the database characteristics. The method with LMDB is at least 3 times faster than that with etree, especially when it is used to read. In addition, the larger the amount of data is processed, the more efficient the method would be.

Seismic data reconstruction based on CS and Fourier theory

Traditional seismic data sampling follows the Nyquist sampling theorem. In this paper, we introduce the theory of compressive sensing （CS）, breaking through the limitations of the traditional Nyquist sampling theorem, rendering the coherent aliases of regular undersampling into harmless incoherent random noise using random undersampling, and effectively turning the reconstruction problem into a much simpler denoising problem. We introduce the projections onto convex sets （POCS） algorithm in the data reconstruction process, apply the exponential decay threshold parameter in the iterations, and modify the traditional reconstruction process that performs forward and reverse transforms in the time and space domain. We propose a new method that uses forward and reverse transforms in the space domain. The proposed method uses less computer memory and improves computational speed. We also analyze the antinoise and anti-aliasing ability of the proposed method, and compare the 2D and 3D data reconstruction. Theoretical models and real data show that the proposed method is effective and of practical importance, as it can reconstruct missing traces and reduce the exploration cost of complex data acquisition.

Improved hybrid iterative optimization method for seismic full waveform inversion

In full waveform inversion （FWI）, Hessian information of the misfit function is of vital importance for accelerating the convergence of the inversion; however, it usually is not feasible to directly calculate the Hessian matrix and its inverse. Although the limited memory Broyden-Fletcher-Goldfarb-Shanno （L-BFGS） or Hessian-free inexact Newton （HFN） methods are able to use approximate Hessian information, the information they collect is limited. The two methods can be interlaced because they are able to provide Hessian information for each other; however, the performance of the hybrid iterative method is dependent on the effective switch between the two methods. We have designed a new scheme to realize the dynamic switch between the two methods based on the decrease ratio （DR） of the misfit function （objective function）, and we propose a modified hybrid iterative optimization method. In the new scheme, we compare the DR of the two methods for a given computational cost, and choose the method with a faster DR. Using these steps, the modified method always implements the most efficient method. The results of Marmousi and overthrust model testings indicate that the convergence with our modified method is significantly faster than that in the L-BFGS method with no loss of inversion quality. Moreover, our modified outperforms the enriched method by a little speedup of the convergence. It also exhibits better efficiency than the HFN method.

Prognostic Significance of Neuroendocrine Differentiation in Non-small Cell Lung Cancer Patients' Survival

Objective： To observe the relationship between non-small cell lung cancer with neuroendrocrine differentiation （NSCLC-NE） and patients＇ postoperative survival. Methods： During April 1997 to April 1999, 98 cases of hlng cancer were surgically treated. The tumor specimens of the patients were stained by NE markers, i.e. neuron specific enolase （NSE） and synaptophysin （SY）. The intensity of NE markers reaction was divided as ＂＋＂. ＂＋＋＂. ＂＋＋＋＂ scale groups. The same specimens were also examined under an electron microscope for the specific neuroendocrine granules. All enrolled patients were followed up for 36 months, and the longest follow-up time was 60 months. The COX proportional hazard model multivariate analysis was applied to observe the relationship between the NSCLE-NE and the patients＇ postoperative survival. Results： In 91 cases of NSCLC, 63.7% （58/91） were positive for NE stain reaction. Among them, 59.3% （54/91） were positive for NSE and 24.1% （22/91） for SY. 48.4% （44/91） were considered as NSCLC-NE by the combination of NE inarker stain reaction and electron microscopic examination. COX proportional hazard model lnnltivariate analysis showed that the NSCLC-NE patients＇ survival was significantly shortened （P=0.048）. The following factors were related to NSCLC-NE patients＇ survival： lung cancer cell differentiation （P=0.006）, clinical lung cancer stage （P=0.001）, the NE markers reaction （P=0.054）. Conclusion： NSCLE-NE is significantly related to the cancer cell differentiation and the patients＇ postoperative survival. The NE markers should be applied clinically as one of prognostic factors to evaluate the postoperative survival of NSCLC patients.

Inter- and intra-hemispheric EEG coherence in patients with mild cognitive impairment at rest and during working memory task

Objective： To assess functional relationship by calculating inter- and intra-hemispheric electroencephalography （EEG） coherence at rest and during a working memory task of patients with mild cognitive impairment （MCI）. Methods： The sample consisted of 69 subjects： 35 patients （n = 17 males, n = 18 females; 52-71 years old） and 34 normal controls （n = 17 males, n = 17 females; 51 -63 years old）. Mini-mental state examination （MMSE） of two groups revealed that the scores of MCI patients did not differ significantly from those of normal controls （P〉0.05）. In EEG recording, subjects were performed at rest and during working memory task. EEG signals from F3-F4, C3-C4, P3-P4, T5-T6 and O1-O2 electrode pairs are resulted from the inter-hemispheric action, and EEG signals from F3-C3, F4-C4, C3-P3, C4-P4, P3-O1, P4-O2, T5-C3, T6-C4, T5-P3 and T6-P4 electrode pairs are resulted from the intra-hemispheric action for delta （1.0-3.5 Hz）, theta （4.0-7.5 Hz）, alpha-1 （8.0-10.0 Hz）, alpha-2 （10.5-13.0 Hz）, beta-1 （13.5-18.0 Hz） and beta-2 （18.5-30.0 Hz） frequency bands. The influence of inter- and intra-hemispheric coherence on EEG activity with eyes closed was examined using fast Fourier transformation from the 16 sampled channels. Results： During working memory tasks, the inter- and intra-hemispheric EEG coherences in all bands were significantly higher in the MCI group in comparison with those in the control group （P〈0.05）. However, there was no significant difference in inter- and intra-hemispheric EEG coherences between two groups at rest. Conclusion： Experimental results comprise evidence that MCI patients have higher degree of functional connectivity between hemispheres and in hemispheres during working condition, It suggests that MCI may be associated with compensatory processes during working memory tasks between hemispheres and in hemispheres. Moreover, failure of normal cortical connections may exist in MCI patients.

The implementation of an improved NPML absorbing boundary condition in elastic wave modeling

In elastic wave forward modeling, absorbing boundary conditions （ABC） are used to mitigate undesired reflections from the model truncation boundaries. The perfectly matched layer （PML） has proved to be the best available ABC. However, the traditional splitting PML （SPML） ABC has some serious disadvantages： for example, global SPML ABCs require much more computing memory, although the implementation is easy. The implementation of local SPML ABCs also has some difficulties, since edges and corners must be considered. The traditional non-splitting perfectly matched layer （NPML） ABC has complex computation because of the convolution. In this paper, based on non-splitting perfectly matched layer （NPML） ABCs combined with the complex frequency-shifted stretching function （CFS）, we introduce a novel numerical implementation method for PML absorbing boundary conditions with simple calculation equations, small memory requirement, and easy programming.

Design and Implementation of a 3D Ocean Virtual Reality and Visualization Engine

In this study,a 3D virtual reality and visualization engine for rendering the ocean,named VV-Ocean,is designed for marine applications.The design goals of VV-Ocean aim at high fidelity simulation of ocean environment,visualization of massive and multidimensional marine data,and imitation of marine lives.VV-Ocean is composed of five modules,i.e.memory management module,resources management module,scene management module,rendering process management module and interaction management module.There are three core functions in VV-Ocean:reconstructing vivid virtual ocean scenes,visualizing real data dynamically in real time,imitating and simulating marine lives intuitively.Based on VV-Ocean,we establish a sea-land integration platform which can reproduce drifting and diffusion processes of oil spilling from sea bottom to surface.Environment factors such as ocean current and wind field have been considered in this simulation.On this platform oil spilling process can be abstracted as movements of abundant oil particles.The result shows that oil particles blend with water well and the platform meets the requirement for real-time and interactive rendering.VV-Ocean can be widely used in ocean applications such as demonstrating marine operations,facilitating maritime communications,developing ocean games,reducing marine hazards,forecasting the weather over oceans,serving marine tourism,and so on.Finally,further technological improvements of VV-Ocean are discussed.

A Method on Extracting Network Connection Information from 64- bit Windows 7 Memory Images

Memory analysis gains a weight in the area of computer live forensics.How to get network connection information is one of the challenges in memory analysis and plays an important role in identifying sources of malicious cyber attack. It is more difficult to fred the drivers and get network connections information from a 64-bit windows 7 memory image file than from a 32-bit operating system memory image f＇de. In this paper, an approach to fred drivers and get network connection information from 64-bit windows 7 memory images is given. The method is verified on 64-bit windows 7 version 6.1.7600 and proved reliable and efficient.

Forward modeling and inversion of tensor CSAMT in 3D anisotropic media

Tensor controlled-source audio-frequency magnetotellurics （CSAMT） can yield information about electric and magnetic fields owing to its multi-transmitter configuration compared with the common scalar CSAMT. The most current theories, numerical simulations, and inversion of tensor CSAMT are based on far-field measurements and the assumption that underground media have isotropic resistivity. We adopt a three-dimensional （3D） staggered-grid finite difference numerical simulation method to analyze the resistivity in axial anisotropic and isotropic media. We further adopt the limited-memory Broyden- Fletcher-Goldfarb-Shanno （LBFGS） method to perform 3D tensor CSAMT axial anisotropic inversion. The inversion results suggest that when the underground structure is anisotropic, the isotropic inversion will introduce errors to the interpretation.

A Memory Efficient Belief Propagation Decoder for Polar Codes

Polar codes have become increasingly popular recently because of their capacity achieving property.In this paper,a memory efficient stage-combined belief propagation(BP) decoder design for polar codes is presented.Firstly,we briefly reviewed the conventional BP decoding algorithm.Then a stage-combined BP decoding algorithm which combines two adjacent stages into one stage and the corresponding belief message updating rules are introduced.Based on this stage-combined decoding algorithm,a memory-efficient polar BP decoder is designed.The demonstrated decoder design achieves 50%memory and decoding latency reduction in the cost of some combinational logic complexity overhead.The proposed decoder is synthesized under TSMC 45 nm Low Power CMOS technology.It achieves 0.96 Gb/s throughput with 14.2mm^2 area when code length N=2^(16)which reduces 51.5%decoder area compared with the conventional decoder design.

Aware conflict detection of non-uniform memory access system and prevention for transactional memory

Most transactional memory (TM) research focused on multi-core processors, and others investigated at the clusters, leaving the area of non-uniform memory access (NUMA) system unexplored. The existing TM implementations made significant performance degradation on NUMA system because they ignored the slower remote memory access. To solve this problem, a latency-based conflict detection and a forecasting-based conflict prevention method were proposed. Using these techniques, the NUMA aware TM system was presented. By reducing the remote memory access and the abort rate of transaction, the experiment results show that the NUMA aware strategies present good practical TM performance on NUMA system.

Fast weighting method for plasma PIC simulation on GPU-accelerated heterogeneous systems

Particle-in-cell (PIC) method has got much benefits from GPU-accelerated heterogeneous systems.However,the performance of PIC is constrained by the interpolation operations in the weighting process on GPU (graphic processing unit).Aiming at this problem,a fast weighting method for PIC simulation on GPU-accelerated systems was proposed to avoid the atomic memory operations during the weighting process.The method was implemented by taking advantage of GPU's thread synchronization mechanism and dividing the problem space properly.Moreover,software managed shared memory on the GPU was employed to buffer the intermediate data.The experimental results show that the method achieves speedups up to 3.5 times compared to previous works,and runs 20.08 times faster on one NVIDIA Tesla M2090 GPU compared to a single core of Intel Xeon X5670 CPU.

An automated method for glacial lake mapping in High Mountain Asia using Landsat 8 imagery

Glacial lakes in the High Mountain Asia(HMA)are sensitive to global warming and can result in much more severe flood disasters than some largesized lakes.An accurate and robust method for the extraction of glacial lakes is critical to effective management of these natural water resources.Conventional methods often have limitations in terms of low spectral contrast and heterogeneous backgrounds in an image.This study presents a robust and automated method for the yearly mapping of glacial lake over a large scale,which took advantage of the complementarity between the modified normalized difference water index(MNDWI)and the nonlocal active contour model,required only local homogeneity in reflectance features of lake.The cloud computing approach with the Google Earth Engine(GEE)platform was used to process the intensive amount of Landsat 8 images from 2015 (344 path/rows and approximately 7504 scenes).The experimental results were validated by very high resolution images from Chinese GaoFen-1 (GF-1) panchromatic multi-spectral(PMS)and appeared a general good agreement.This is the first time that information regarding the spatial distribution of glacial lakes over the HMA has been derived automatically within quite a short period of time.By integrating it with the relevant indices,it can also be applied to detect other land cover types such as snow or vegetation with improved accuracy.

Clinical and pathological characteristics of intraductal proliferative lesions and coexist with invasive ductal carcinomas

Objective： The purpose of this study was to study the clinical and pathological characteristics of breast intraductal proliferative lesions （IDPLs） and associated with invasive breast cancer. Methods： We reviewed 327 cases of breast intra- ductal proliferative lesions including 53 cases of usual ductal hyperplasia, 57 cases of atypical ductal hyperplasia, 89 cases of ductal carcinoma in situ, and 128 cases coexist with invasive ductal carcinomas. Cases of pure invasive cancer without intraductal proliferative lesions were excluded. The mult IDPLs biological parameters including the express of ER, PR, HER2, HIF-lo and Ki-67 detected by immunohistochemistry S-P method （n = 327） and the levels of CA153, TSGF, CA125 and CEA both in nipple discharge and serum （n = 179） measured with Electrochemiluminescence method and their relationship were studied, and 30 cases of normal pregnant women were compared with. Results： A single histologic subtype was present in 49.85% （163/327） of the cases, two subtypes in 33.03% （108/327）, and three in 17.13% （56/327）. The most common subtypes present were cribriform （43.12%, 141/327） and solid （38.53%, 126/327）, while the comedo （16.35%, 54/327）, and micropapillary （12.84%, 42/327） subtypes were less common. Comedo and solid were frequently found together for coexpres- sion as were micropapillary and papillary subtypes. However, Comedo subtype was much less likely to be found with papillary, cribriform or micropapillary subtypes. Additionally, comedo subtypes tend to be hormone receptor negative, Her2 positive and high-grade while the cribriform and solid subtype tends to be hormone receptor positive, Her2 negative and low grade. Papil- lary subtype was least likely to be associated with an invasive cancer. Furthermore, the nipple discharge and serum levels of CA153, TSGF, CA125 and CEA in coexist with invasive ductal carcinomas patients were significantly higher than those in the benign breast disease （pure intraductal proliferative lesions） and normal pregnant women （P 〈 0.01）. Additionally, the levels of CA153, TSGF, CA125 and CEA in nipple discharge were significantly higher than in the serum （P 〈 0.01）, and had a positive correlation with the Ki-67, grade, clinical stage, lymph node metastasis and tumor recurrence （P 〈 0.05）, and negative correla- tion with the level of ER and PR （P 〈 0.05）. The sensitivity of the four serum tumor markers in combination was only 69.77%, in contrast, the combined detection both in discharge and serum was 97.67%, and the negative predictive value was 99.03%. The sensitivity of combined detection both in nipple discharge and serum were significantly higher than other detection （P 〈 0.05）. Conclusion： IDPLs often present more than one histologic subtype and the most common subtypes are cribriform and solid, while comedo and micropapillary subtypes are less common. Our results suggest that the levels of CA153, TSGF, CA125 and CEA in nipple discharge were significantly higher than those in the serum, and is associated with HIF-le. The aberration of HIF-la may play a key role during oncogenesis and promote breast cellular transformation into malignancy, a finding useful for further understanding of tumorigenesis. Nipple discharge can be the earliest presenting symptom of breast cancer. The dynamic combined detection of the four tumor markers both in nipple discharge and serum are helpful to the stratification of preoperative patients and benefit to better prewarning markers for monitoring their recurrence and metastasis and clinical staging of tumors in clinic, but cannot increase the sensitivity of judging the patients with early breast cancer.

Improved Adaptive Random Convolutional Network Coding Algorithm

To address the issue of field size in random network coding, we propose an Improved Adaptive Random Convolutional Network Coding (IARCNC) algorithm to considerably reduce the amount of occupied memory. The operation of IARCNC is similar to that of Adaptive Random Convolutional Network Coding (ARCNC), with the coefficients of local encoding kernels chosen uniformly at random over a small finite field. The difference is that the length of the local encoding kernels at the nodes used by IARCNC is constrained by the depth; meanwhile, increases until all the related sink nodes can be decoded. This restriction can make the code length distribution more reasonable. Therefore, IARCNC retains the advantages of ARCNC, such as a small decoding delay and partial adaptation to an unknown topology without an early estimation of the field size. In addition, it has its own advantage, that is, a higher reduction in memory use. The simulation and the example show the effectiveness of the proposed algorithm.

Design of small-area multi-bit antifuse-type 1 kbit OTP memory

A multi-bit antifuse-type one-time programmable （OTP） memory is designed, which has a smaller area and a shorter programming time compared with the conventional single-bit antifuse-type OTP memory. While the conventional antifuse-type OTP memory can store a bit per cell, a proposed OTP memory can store two consecutive bits per cell through a data compression technique. The 1 kbit OTP memory designed with Magnachip 0.18 μm CMOS （complementary metal-oxide semiconductor） process is 34% smaller than the conventional single-bit antifuse-type OTP memory since the sizes of cell array and row decoder are reduced. And the programming time of the proposed OTP memory is nearly 50% smaller than that of the conventional counterpart since two consecutive bytes can be compressed and programmed into eight OTP cells at once. The layout area is 214 μm× 327 μ,, and the read current is simulated to be 30.4 μA.

Modified Self-adaptive Immune Genetic Algorithm for Optimization of Combustion Side Reaction of p-Xylene Oxidation

In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.