Extending parallelization of the self-organizing map by combining data and network partitioned methods

High-dimensional data is pervasive in many fields such as engineering, geospatial, and medical. It is a constant challenge to build tools that help people in these fields understand the underlying complexities of their data. Many techniques perform dimensionality reduction or other “compression” to show views of data in either two or three dimensions, leaving the data analyst to infer relationships with remaining independent and dependent variables. Contextual self-organizing maps offer a way to represent and interact with all dimensions of a data set simultaneously. However, computational times needed to generate these representations limit their feasibility to realistic industry settings. Batch self-organizing maps provide a data-independent method that allows the training process to be parallelized and therefore sped up, saving time and money involved in processing data prior to analysis. This research parallelizes the batch self-organizing map by combining network partitioning and data partitioning methods with CUDA on the graphical processing unit to achieve significant training time reductions. Reductions in training times of up to twenty-five times were found while using map sizes where other implementations have shown weakness. The reduced training times open up the contextual self-organizing map as viable option for engineering data visualization.     

Equivalence relations among interconnection networks

The interconnection network equivalence notions reported in the literature are formalized via conjugation maps over the sets of interconnections of such networks. Various forms of relations including group isomorphisms among interconnection networks are introduced. Equivalence relations express the degrees of freedom in “making one network behave like another.” Examples of these relations for commutative cube-connected networks with individual stage control are also included. In addition, an algorithm is provided to construct equivalence maps among such networks.     

Utilization of data access and manipulation in conceptual schema definitions

The basic idea of this approach is to use data access and manipulation functions in data definition, such that testing a given individual data object on its conformance to data definition is done by running a (finally boolean) procedure against it. In essence, schema entries (i.e. definitions, declarations, etc.) are viewed as expressions of predicate logic where the individuals are obtained by the execution of data manipulation operations which include a rather general information selection technique or conceptual access method.Selection of information constructs in databases usually adopts a technique closely tailored to the specific “data model”. It is one of the intentions of this paper to demonstrate the common principles behind the variety of selection techniques by a uniform approach which comprises the selection features of most of the database management systems and makes them comparable.At the level of information structure a kind of “geography” is introduced into a database, which allows to distinguish the same information construct (record, file, segment, item, coset, tuple,…) in distinct information contexts or at distinct conceptual locations called “spots”. By definition, every spot (“construct in/with context”) exists only once in a given database. In combination with some basic operators a logical addressing mechanism has been designed, which follows the context of a construct to identify it within this very context. This algorithm turns out to be a general vehicle to locate a construct at a spot, independently of whether the database has a relational, network, hierarchical or any other appearance.The method of context directed addressing along with pertinent operators allows in a very general way—i.e. neither biased nor restricted to a “data model”—to define types of information constructs and of construct transitions as is required in a conceptual community schema. This is demonstrated through examples of schema entries with rather complex cross-consistency conditions and additional transition rules called persistency conditions. The examples also intend to give an idea of the minimum support to be expected from any future conceptual schema language.     

A computer procedure to analyze seismic data to estimate outcome probabilities in oil exploration,with an initial application in the tabasco region of southeastern Mexico

The Tabasco region contains a number of major oilfields, including some of the emerging “giant” oil fields which have received extensive publicity. Fields in the Tabasco region are associated with large geologic structures which are detected readily by seismic surveys. The structures seem to be associated with deepseated movement of salt, and they are complexly faulted. Some structures have as much as 1000 milliseconds relief of seismic lines. A study, interpreting the structure of the area, used initially only a fraction of the total seismic linesThat part of Tabasco region that has been studied was surveyed with a close-spaced rectilinear network of seismic lines. A, interpreting the structure of the area, used initially only a fraction of the total seismic data available. The purpose was to compare “predictions” of reflection time based on widely spaced seismic lines, with “results” obtained along more closely spaced lines. This process of comparison simulates the sequence of events in which a reconnaissance network of seismic lines is used to guide a succession of progressively more closely spaced lines. A square gridwork was established with lines spaced at 10 km intervals, and using machine contour maps, compared the results with those obtained with seismic grids employing spacings of 5 and 2.5 km respectively.The comparisons of predictions based on widely spaced lines with observations along closely spaced lines provide information by which an error function can be established. The error at any point can be defined as the difference between the predicted value for that point, and the subsequently observed value at that point. Residuals obtained by fitting third-degree polynomial trend surfaces were used for comparison. The root mean square of the error measurement, (expressed in seconds or milliseconds reflection time) was found to increase more or less linearly with distance from the nearest seismic point. Oil-occurrence probabilities were established on the basis of frequency distributions of trend-surface residuals obtained by fitting and subtracting polynomial trend surfaces from the machine-contoured reflection time maps. We found that there is a strong preferential relationship between the occurrence of petroleum (i.e. its presence versus absence) and particular ranges of trend-surface residual values. An estimate of the probability of oil occurring at any particular geographic point can be calculated on the basis of the estimated trend-surface residual value. This estimate, however, must be tempered by the probable error in the estimate of the residual value provided by the error function.The result, we believe, is a simple but effective procedure for estimating exploration outcome probabilities where seismic data provide the principal form of information in advance of drilling. Implicit in this approach is the comparison between a maturely explored area, for which both seismic and production data are available, and which serves as a statistical “training area”, with the “target” area which is undergoing exploration and for which probability forecasts are to be calculated.     

Optimizing Remote File Access for Parallel and Distributed Network Applications

This paper presents a paradigm for remote file access called Smart File Objects (SFOs). The SFO is a realization of the ELFS (Extensible File Systems) concept of files as typed objects, but it is applied to wide-area networks (J. Karpovich et al., in “Proceedings of the 9th OOPLSA,” 1994). The SFO is an object-oriented application- specific file access paradigm designed to address the bottleneck imposed by high latency, low bandwidth, unpredictable, and unreliable networks such as the current Internet. Newly emerging network applications such as multimedia, metacomputing, and collaboratories will have different sensitivities to these network “features.” These applications will require a more flexible file access mechanism than what is provided by conventional distributed file systems. The SFO uses application and network information to adaptively prefetch and cache needed data in parallel with the execution of the application to mitigate the impact of the network. Preliminary results indicate that the SFO can provide substantial performance gains for network applications.     

基于特征标识的文件类型识别与匹配

不同类型文件的识别与匹配是计算机文件系统中一个重要问题,一般分为特征标识(魔数)和后缀名两种方式,其中后者是被广泛接受的一种方式.然而在使用过程中,经常遇见文件名被篡改或损坏、文件后缀名缺失而无法被系统自动识别的情况,此时无法正常打开、浏览或编辑文件.文件头的特征标识将文件特征信息存储于文件数据内部,不容易被修改或损坏...     

Difficulty control for blockchain-based consensus systems

Crypto-currencies like Bitcoin have recently attracted a lot of interest. A crucial ingredient into such systems is the “mining” of a Nakamoto blockchain. We model mining as a Poisson process with time-dependent intensity and use this model to derive predictions about block times for various hash-rate scenarios (exponentially rising hash rate being the most important). We also analyse Bitcoin’s method to update the “network difficulty” as a mechanism to keep block times stable. Since it yields systematically too fast blocks for exponential hash-rate growth, we propose a new method to update difficulty. Our proposed method performs much better at ensuring stable average block times over longer periods of time, which we verify both in simulations of artificial growth scenarios and with real-world data. Besides Bitcoin itself, this has practical benefits particularly for systems like Namecoin. It can be used to make name expiration times more predictable, preventing accidental loss of names.     

Evocation: analyzing and propagating a semantic link based on free word association

Studies of lexical–semantic relations aim to understand the mechanism of semantic memory and the organization of the mental lexicon. However, standard paradigmatic relations such as “hypernym” and “hyponym” cannot capture connections among concepts from different parts of speech. WordNet, which organizes synsets (i.e., synonym sets) using these lexical–semantic relations, is rather sparse in its connectivity. According to WordNet statistics, the average number of outgoing/incoming arcs for the hypernym/hyponym relation per synset is 1.33. Evocation, defined as how much a concept (expressed by one or more words) brings to mind another, is proposed as a new directed and weighted measure for the semantic relatedness among concepts. Commonly applied semantic relations and relatedness measures do not seem to be fully compatible with data that reflect evocations among concepts. They are compatible but evocation captures MORE. This work aims to provide a reliable and extendable dataset of concepts evoked by, and evoking, other concepts to enrich WordNet, the existing semantic network. We propose the use of disambiguated free word association data (first responses to verbal stimuli) to infer and collect evocation ratings. WordNet aims to represent the organization of mental lexicon, and free word association which has been used by psycholinguists to explore semantic organization can contribute to the understanding. This work was carried out in two phases. In the first phase, it was confirmed that existing free word association norms can be converted into evocation data computationally. In the second phase, a two-stage association-annotation procedure of collecting evocation data from human judgment was compared to the state-of-the-art method, showing that introducing free association can greatly improve the quality of the evocation data generated. Evocation can be incorporated into WordNet as directed links with scales, and benefits various natural language processing applications.     

Multi-VMap: A Multi-Scale Model for Vector Maps

Multi-VMap is a compact framework from which plane graphs representing geographic maps at different levels of detail can be extracted. Its main feature is that the scale of the extracted map can be variable through its domain, while each entity maintains consistent combinatorial relations with the rest of entities represented in the map. The model is based on a set of operators, called updates, which modify the level of detail in a small portion of a map. The set of updates is partially ordered, and can therefore be represented as a Directed Acyclic Graph, which defines our multi-scale structure. An algorithm to extract a map at the required resolution is proposed, and a lower bound for the number of different maps which can be extracted from the model is given. The model supports map data processing operations (e.g., querying), as well as progressive and selective transmission of maps over a network.     

基于RTF格式的文本脆弱水印算法

文本水印算法容易受到格式化和存储攻击。该文提出一种基于RTF格式的文本脆弱水印算法，能够抵抗格式化和存储攻击，并且对文本段落拷贝时，文本水印不丢失。对文本段落的任何修改都能在水印提取验证段检测出来。分析了3种水印攻击手段。介绍了该水印的实现算法，并对文本水印攻击检测给出了实验结果。     

AutoCAD在地质图制图中的应用

介绍了利用AutoCAD软件制作地质图件过程中应注意和掌握的几个要点：如坐标对应转换方法、精确定位方法、块的应用、图案填充在地质剖面图中的使用及自定义图案等,及AutoCAD软件生成的dwf格式的图件和№旺璐软件的wl、wt文件之间转换时的参数设置。     

面向图像分类的基于注意力引导的Dropout

当一个较大的神经网络在较少的训练数据上训练时,不可避免的会遭遇过拟合问题,进而在测 试数据集上泛化性能较差。因此,提出了多种基于 Dropout 的正则化方法来缓解这个问题。虽然,这些方法不 能直接促使模型关注有较低判别力的特征,但对减少过拟合同样非常重要。为解决该问题,提出了一种基于注 意力引导的 Dropout (AD),利用自监督机制更高效地缓解特征描述算子之间的协同自适应问题。AD 包含 2 个 独特的组件：①特征的重要性度量机制,通过 SE-Block 度量得到每个特征的重要程度;②基于可学习丢弃概 率的 Dropout,通过丢弃“较好”的特征检测算子,强迫“较差”的特征检测算子学习到一个较好的特征表示, 从而缓解特征检测算子之间的协同自适应并促使模型学习拥有较低判别力的特征。实验结果表明该方法可以容 易地被应用到各种卷积神经网络(CNN)结构里,并获得较好的性能。     

A Neural Network Method for Efficient Vegetation Mapping

This article describes the application of a neural network method designed to improve the efficiency of map production from remote sensing data. Specifically, the ARTMAP neural network produces vegetation maps of the Sierra National Forest, in Northern California, using Landsat Thematic Mapper (TM) data. In addition to spectral values, the data set includes terrain and location information for each pixel. The maps produced by ARTMAP are of comparable accuracy to maps produced by a currently used method, which requires expert knowledge of the area as well as extensive manual editing. In fact, once field observations of vegetation classes had been collected for selected sites, ARTMAP took only a few hours to accomplish a mapping task that had previously taken many months. The ARTMAP network features fast online learning, so that the system can be updated incrementally when new field observations arrive, without the need for retraining on the entire data set. In addition to maps that identify lifeform and Calveg species, ARTMAP produces confidence maps, which indicate where errors are most likely to occur and which can, therefore, be used to guide map editing.     

An Optimization Approach to Improving Collections of Shape Maps

Finding an informative, structure‐preserving map between two shapes has been a long‐standing problem in geometry processing, involving a variety of solution approaches and applications. However, in many cases, we are given not only two related shapes, but a collection of them, and considering each pairwise map independently does not take full advantage of all existing information. For example, a notorious problem with computing shape maps is the ambiguity introduced by the symmetry problem — for two similar shapes which have reflectional symmetry there exist two maps which are equally favorable, and no intrinsic mapping algorithm can distinguish between them based on these two shapes alone. Another prominent issue with shape mapping algorithms is their relative sensitivity to how “similar” two shapes are — good maps are much easier to obtain when shapes are very similar. Given the context of additional shape maps connecting our collection, we propose to add the constraint of global map consistency, requiring that any composition of maps between two shapes should be independent of the path chosen in the network. This requirement can help us choose among the equally good symmetric alternatives, or help us replace a “bad” pairwise map with the composition of a few “good” maps between shapes that in some sense interpolate the original ones. We show how, given a collection of pairwise shape maps, to define an optimization problem whose output is a set of alternative maps, compositions of those given, which are consistent, and individually at times much better than the original. Our method is general, and can work on any collection of shapes, as long as a seed set of good pairwise maps is provided. We demonstrate the effectiveness of our method for improving maps generated by state‐of‐the‐art mapping methods on various shape databases.     

信息安全存储的初步研究与应用

在信息化社会中 ,信息安全防卫扮演着重要角色。信息安全可以从三方面加以考虑 ,即网络安全、系统安全和安全存储。文章对安全存储进行了探讨 ,并分析了威胁安全存储的主要因素 ,及安全存储的基本要求和基本对策。作为安全存储的应用 ,文中分析了“文件保险箱”和“文件安全删除工具”的设计思路 ,并介绍了其实现方法     

Supervised semantic labeling of places using information extracted from sensor data

Indoor environments can typically be divided into places with different functionalities like corridors, rooms or doorways. The ability to learn such semantic categories from sensor data enables a mobile robot to extend the representation of the environment facilitating interaction with humans. As an example, natural language terms like “corridor” or “room” can be used to communicate the position of the robot in a map in a more intuitive way. In this work, we first propose an approach based on supervised learning to classify the pose of a mobile robot into semantic classes. Our method uses AdaBoost to boost simple features extracted from sensor range data into a strong classifier. We present two main applications of this approach. Firstly, we show how our approach can be utilized by a moving robot for an online classification of the poses traversed along its path using a hidden Markov model. In this case we additionally use as features objects extracted from images. Secondly, we introduce an approach to learn topological maps from geometric maps by applying our semantic classification procedure in combination with a probabilistic relaxation method. Alternatively, we apply associative Markov networks to classify geometric maps and compare the results with a relaxation approach. Experimental results obtained in simulation and with real robots demonstrate the effectiveness of our approach in various indoor environments.     

Three‐dimensional map building for mobile robot navigation environments using a self‐organizing neural network

In recent years, mobile robots have been required to become more and more autonomous in such a way that they are able to sense and recognize the three‐dimensional space in which they live or work. In this paper, we deal with such an environment map building problem from three‐dimensional sensing data for mobile robot navigation. In particular, the problem to be dealt with is how to extract and model obstacles which are not represented on the map but exist in the real environment, so that the map can be newly updated using the modeled obstacle information. To achieve this, we propose a three‐dimensional map building method, which is based on a self‐organizing neural network technique called “growing neural gas network.” Using the obstacle data acquired from the 3D data acquisition process of an active laser range finder, learning of the neural network is performed to generate a graphical structure that reflects the topology of the input space. For evaluation of the proposed method, a series of simulations and experiments are performed to build 3D maps of some given environments surrounding the robot. The usefulness and robustness of the proposed method are investigated and discussed in detail. © 2004 Wiley Periodicals, Inc.     

The Relationship between Transport Wireless Network Throughput and Vehicle Speed

The article describes determined relationship between transport wireless network throughput and vehicle’s velocity. It is determined that such relationship is most precisely described by quadratic polynomial function, which was obtained by processing experimentally measured data and approximating them with various functions. When evaluating network’s throughput with “application layer” and “transport layer” software, the highest layer overheads can be determined. As it was stated, they form a great part of transmitted traffic. It must be considered in practice, because network’s throughput cannot be determined only by measurements of OSI Layer 3 or Layer 4 throughput.     

Web数据库环境中分子结构式的处理

讨论了在Web数据库环境中处理分子结构式的问题。分子结构式可存储为静态图片格式或动态结构式格式。静态图片格式具有平台无关性,动态结构式格式则具有可编辑性及动态显示的优势。在关系数据库中,既可将分子式文件名或所在路径作为数据项,也可直接将分子式方 本身作为数据项。文中给出将分子式文件存入数据库的程序流程的示例,使用插件（Plug-in）或ActiveX控件,可在Web浏览器中直接显示动态的分子结构式,文中分析了二者处的优势,并结合ASP和Chime插件技术,给出了在数据库中检索分子结构式的具体实现方法。