ppxscal/embedding_network huggingface dataset:
GridIJ - A Dynamic Grid Service Architecture for Scientific Image Processing
Authors: Alexander Frank, Rainer Stotzka, Thomas Jejkal, Volker Hartmann, Michael Sutter, Hartmut Gemmeke
Venue: Proceedings of the 33rd EUROMICRO Conference on Software Engineering and Advanced Applications (2007)

The presented dynamic Grid service architecture provides a novel and comfortable access for scientific software developers and users without prior knowledge of Grid technologies or even the underlying architecture. A simple Java API allows the extension of WSRF - compliant web services by scientific software components deployed automatically on available GT4 containers. In preparation only two services are started on each container allowing hot - deployment and simple performance analysis. GridIJ is a reference implementation of the presented architecture with a problem solving environment for image processing. A plugin with a GUI extends the free software ImageJ, providing control of the architecture, deploying scientific software components (GridPlugins), distributing data to process in parallel, controlling the workflow and returning the results. First tests showed the simple usage and extension by GridPlugins of the system. In principle the performance in parallel execution scales linearly with an additional small overhead for connecting and data transfer.
Real-time Terrain Deformations
Authors: Radim Dvorak, Martin Drahansky
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

This paper presents a method for a physically based real-time terrain deformation. The motivation originates from the fact that there exist many deformable models, but the terrain deformation is a special problem in the field of computer graphics. OpenSceneGraph toolkit provides an excellent environment for the large terrain visualization and it was accepted as a standard for many graphic specialists. Therefore, the main goal of this method is the local deformation ability of some large terrain, which is represented by a sub-graph of OpenSceneGraph scene. However, the technique may be easily adaptable to any terrain representation. The results show a great potential of the used method and thus there is outlined the future work at the end.
A Metamodeling Approach to Tracing Variability between Requirements and Architecture in Software Product Lines
Authors: Mikyeong Moon, Heung Seok Chae, Taewoo Nam, Keunhyuk Yeom
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Even in traditional single software product development, failure to manage changes in requirements can cause degeneration of the architecture and components. Traceability issues are even more important in the product line because the impact of changes in a product line can involve all the product line-based applications. Variability means the ability of a software system to be changed, customized or configured for use in a particular context and it should be managed at different levels of abstraction. In this paper, we suggest a metamodeling approach to support the tracing of the variability in requirements and architecture. Two metamodels representing the domain requirements and domain architecture with variability are proposed. Based on the proposed metamodels, we describe trace relationships between requirements and architecture with respect to variability.
Kernel based Learning Suitable for Text Categorization
Authors: Taeho Jo, Malrey Lee
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

This research proposes a new strategy where documents are encoded into string vectors for text categorization and modified versions of SVM to be adaptable to string vectors. Traditionally, when the supervised machine learning algorithms are used for pattern classification, raw data should be encoded into numerical vectors. This encoding may be difficult, depending on a given application area of pattern classification. For example, in text categorization, encoding full texts given as raw data into numerical vectors leads to two main problems: huge dimensionality and sparse distribution. In this research, we encode full texts into string vectors, and apply the SVM to string vectors for text categorization.
Context Modeling for MRI Denoising in the Undecimated Wavelet Domain
Authors: Lina Tan, Xieping Gao, Shengming He, Fei Li
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

In Magnetic Resonance Imaging(MRI), the acquired complex valued data obtained as the inverse fourier transform of the raw k-space data are corrupted by Gaussian distributed noise. In this letter, we present an adaptive neighborhood selection algorithm by accounting for the spatial context information, calculated in the undecimated wavelet domain. A modified Wiener filter is approached by a novel bivariate thresholding, considering local signal variance by valid information from the selected neighborhood windows. In contrast to the previously proposed methods in the literature, our scheme can preserve edges more effectively while suppressing noise and artifacts; moreover, both the SNR and RMSE are improved obviously.
Image Composition via Lookup Table Manipulation
Authors: James Foley, Won Kim
Venue: IEEE Computer Graphics and Applications (1987)

The Image Composition Language provides a convenient way for programmers of interactive graphics application programs to define how the video lookup table of a raster display system is to be loaded. ICL allows one or several images stored in the frame buffer to be combined or modified in a variety of ways. ICL treats these images as variables, and provides arithmetic, relational, and conditional operators to combine the images, scalar variables, and constants in such image composition expressions as old_image*t+new_image*(1.0-t) and ifimager>0.5thenimage ¿ {0.5,0,0,} else image endif. Use of the Image Composition Language relieves programmers of the tedium usually associated with loading the video lookup table to do simple image composition and modification.
Contextual Word Recognition Using Binary Digrams
Authors: E. M. Riseman, R. W. Ehrich
Venue: IEEE Transactions on Computers (1971)

This paper describes a special-purpose character recognition system which uses contextual information for the recognition of words from any given dictionary of words. Previous techniques that utilized context involved letter transition probabilities of digrams and trigrams. This research introduces the concept of binary digrams which overcomes some of the problems of past approaches. They can be used to extract offectively the "syntax" of the dictionary while requiring very modest amounts of storage. A computationally feasible procedure is described which allows the accuracy requirements of the character recognizer to be relaxed if it is followed by a contextual postprocessor. The modified recognition system is allowed to output several alternatives for each character, while the postprocessor selects the proper string of characters by having access to both the dictionary and the dictionary syntax. A theoretical estimate of the recognition rate is derived, and experimental results demonstrate the ability of the system to achieve low error and rejection rates.
Control Storage Use in Implementing an Associative Memory for a Time-Shared Processor
Authors: L. Hellerman, G. E. Hoernes
Venue: IEEE Transactions on Computers (1968)

Abstract The Cambridge System, comprising a standard IBM System/360 Model 40 and an associative memory, is described from the viewpoint of its implementation using the READ-only control storage of the Model 40. In particular, we discuss the use of the ROS in 1) controlling the flow of data between the CPU and the associative memory registers, and 2) handling translation control, absent page indications, and variable field operand pretesting, when the associative memory is used for page translation in a time-sharing mode of operation. Although the main use of the system is as a computer facility that may be shared simultaneously by up to fifteen users, it may also be used as an ordinary batch processor having a small experimental associative memory among its facilities. The magnitude of the ROS additions and modifications, in terms of numbers of microinstructions, is given.
Fuzzy gain scheduling for position control of a robot manipulator
Authors: M. Alata, M. Jarrah, K. Demirli, A. Bulgak
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2000)

This paper presents an interactive procedure for controller design for nonlinear system by integrating available classical as well as modern tools such as fuzzy logic, and neural networks. The proposed approach is based on quasi-linear dynamic models of the plant. Classical optimal controllers for each set of operating conditions were developed. These controllers are used to construct a single fuzzy-logic gain scheduling-like controller. Adaptive-neuro-fuzzy inference system was used to construct the rules for the fuzzy gain schedule. This will guarantee the continuos change in the gains as the system parameters change in time or space. This procedure is systematic and can be used to design controllers for many nonlinear systems. Two degrees of freedom (dof) planar manipulator was chosen to show the effectiveness of the proposed approach. A robot manipulator is inherently unstable and displays a strong nonlinearity. The resulting system is stable for different reference trajectories. The system is also robust for wide range of driving frequencies of the input. This system is able to deal with slow as well as fast varying systems, which is a significant improvement on conventional gain scheduling.
The Neural Circuits Designing and Analysis by the Universal Fuzzy Logical Framework
Authors: Hong Hu, Zhongzhi Shi
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Analytical study or designing of large-scale nonlinear neural circuits, especially for chaotic neural circuits, is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system, and we proved that if a neural system works in a non-chaotic way, a suitable fuzzy logical framework can be found and we can analyze or design such kind neural system similar to analyze or design a digit computer, but if a neural system works in a chaotic way, a granular approximation is needed for understanding the function of such neural system. Key words: fuzzy logic, neural dynamic analysis, granular approximation
Enhanced Range finding Algorithms for Equidistance Stereo Catadioptric Mirrors
Authors: Young-ho Choi, Min-goo Kang
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

Catadioptric mirrors are widely used in automatic surveillance system. The major drawback of catadioptric mirror is its unequal image resolution. Even double panoramic structure can generate stereo images with single camera system. So two images obtained from double panoramic equidistance catadioptric mirror can be used in finding the depth and height values of object's points. Equidistance catadioptric mirror can be the solution to this problem. But compared to the single catadioptric mirror, the image size of double panoramic system is relatively small. This leads to the severe accuracy problem in estimation. The exact axial alignment and the exact mount of mirror are the sources that can be avoided but the focal length variation is inevitable. In this paper, the effects of focal length variation on the computation of depth and height of object' point are explained and the effective focal length finding algorithm, using the assumption that the object's viewing angles are almost same in stereo images, is presented.
Efficient Transformation Scheme for Indexing Continuous Queries on RFID Streaming Data
Authors: Jaekwan Park, Bonghee Hong, Chaehoon Ban
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

RFID data are usually regarded as streaming data that are huge and change frequently because they are gathered continuously by numerous readers. RFID middleware filters the data acquired from the readers to process queries from applications. To enhance the performance of the middleware, an index must be built to process the queries efficiently. Several approaches to building an index on queries rather than data records, called query index, have been proposed and are widely used to evaluate continuous queries over streaming data. EPCglobal proposed an Event Cycle Specification (ECSpec) model, which is a standard query interface for RFID applications. The problem with using any of the query indexes in the ECSpec model is that it takes a long time to build the index and to process queries because each data consist of a large number of segments. To solve this problem, we propose an aggregate transformation that converts a group of segments into compressed data. Then, we measure the performance improvement of the index by the proposed technique using experimental evaluation.
A New Method Based on Genetic Algorithm for Reduction of Attribution under Incomplete Decision-Making Table
Authors: Ke Luo, Huaimeng Ji, Ping Fu, Xiaojiao Tong
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

Under incomplete information system, the reduction of attribution based on rough set theory is an important but difficult task, and researches have already proved that finding minimal relative reduction is the NP complete question. Regarding to the complete decision-making table, there have been many methods to find the minimal relative reduction, but for incomplete decision-making tables, researches on this aspect are quite few. By defining approximate classified precision and the approximate classified quality of the consistent relation class, combining global optimization and connotative parallel characteristic of the genetic algorithm, adopting the most super preserved strategy, we proposed an attribute reduction method to focus on incomplete decision-making table. The result of the experiment showed that this algorithm has good solution ability, no matter whether the decision-making table is consistent or not, it can find the minimal relative reduction.
Triangle-free distance-regular graphs with an eigenvalue multiplicity equal to their valency and diameter 3
Authors: Aleksandar Jurišić, Jack Koolen, Arjana itnik
Venue: European Journal of Combinatorics (2008)

In this paper, triangle-free distance-regular graphs with diameter 3 and an eigenvalue @q with multiplicity equal to their valency are studied. Let @C be such a graph. We first show that @q=-1 if and only if @C is antipodal. Then we assume that the graph @C is primitive. We show that it is formally self-dual (and hence Q-polynomial and 1-homogeneous), all its eigenvalues are integral, and the eigenvalue with multiplicity equal to the valency is either second largest or the smallest. Let x,y@?V@C be two adjacent vertices, and z@?@C"2(x)@?@C"2(y). Then the intersection number @t"2@?|@C(z)@?@C"3(x)@?@C"3(y)| is independent of the choice of vertices x, y and z. In the case of the coset graph of the doubly truncated binary Golay code, we have b"2=@t"2. We classify all the graphs with b"2=@t"2 and establish that the just mentioned graph is the only example. In particular, we rule out an infinite family of otherwise feasible intersection arrays.
Hands-on with the NetFPGA to build a Gigabit-rate Router
Authors: Nick McKeown, John W. Lockwood, Jad Naous, Glen Gibb, Adam Covington
Venue: Proceedings of the 15th Annual IEEE Symposium on High-Performance Interconnects (2007)

An open platform called the NetFPGA has been developed at Stanford University. The NetFPGA platform enables researchers and instructors to build high-speed, hardware-accelerated networking systems. The platform can be used in the classroom to teach students how to build Ethernet switches and Internet Prototcol (IP) routers using hardware rather than software. The platform can be used by researchers to prototype advanced services for next-generation networks.
A Low-Power Application Specific Instruction Set Processor Using Asynchronous Function Units
Authors: Yong Li, Zhi-ying Wang, Kui Dai
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Low-power design became crucial with widespread use of the embedded systems. The embedded processors need to be efficient in order to achieve real-time requirements with low power consumption for specific algorithms. As the superset of traditional very long instruction word (VLIW) architecture, the main advantages of Transport Triggered Architecture (TTA) are its simplicity and flexibility. In TTA processors, the special function units can be utilized to in- crease performance or reduce power dissipation. Asyn- chronous circuits have characteristic of low power con- sumption and it is possible to exploit this characteristic to design embedded processors. In this article, we designed a low-power embedded processor using asynchronous func- tion units. The processor core is globally synchronous and locally asynchronous implementation using not only synchronous function units but also asynchronous function units. We also presented an efficient design flow that use asynchronous circuits in TTA framework, which is only a synchronous design environment. The test result shows that this processor has lower power dissipation than its pure synchronous version that only uses synchronous function units.
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
Authors: Ping Li, Trevor J. Hastie, Kenneth W. Church
Venue: The Journal of Machine Learning Research (2007)

For dimension reduction in the l1 norm, the method of Cauchy random projections multiplies the original data matrix A ∈ ℝn×D with a random matrix R ∈ ℝD×k (k≪D) whose entries are i.i.d. samples of the standard Cauchy C(0,1). Because of the impossibility result, one can not hope to recover the pairwise l1 distances in A from B=A×R∈ ℝn×k, using linear estimators without incurring large errors. However, nonlinear estimators are still useful for certain applications in data stream computations, information retrieval, learning, and data mining. We study three types of nonlinear estimators: the sample median estimators, the geometric mean estimators, and the maximum likelihood estimators (MLE). We derive tail bounds for the geometric mean estimators and establish that k = O(log n / ε2) suffices with the constants explicitly given. Asymptotically (as k→∞), both the sample median and the geometric mean estimators are about 80% efficient compared to the MLE. We analyze the moments of the MLE and propose approximating its distribution of by an inverse Gaussian.
Estimation of Net Primary Production of the Kii Peninsula Using Terra/MODIS Data
Authors: Yi Cen, Kanako Muramatsu, Liangpei Zhang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

Precise estimations of zonal net primary production (NPP) are vital for understanding global carbon circulation. To estimate NPP, light use efficiency (LUE) model using normalized differential vegetation index (NDVI) has been used mainly. NDVI is obtained from red and near-infrared channels only, however, recent sensors onboard satellites always have hyper-multi-spectral channels; In order to use these data effectively, which include more details about land cover, a vegetation index based on pattern decomposition method (VIPD) has been set up to estimate NPP. The present study used 2001 Terra/MODIS (Moderate Resolution Imaging Spectroradiometer) data for the Kii Peninsula, which is mainly covered by temperate forest. To validate the proposed method, we compared the satellite data-based NPP values for the evergreen with values derived from land-survey data. The proposed method estimated the annual NPP of a temperate forest on Yoshino Mountain to be 1.52 ± 0.39 kg CO2/m2/year, which agreed with the ground-survey result of 1.50 ± 0.75 kg CO2/m2/year, within the algorithm error. An average zonal NPP of 1.55 ± 0.40 kg CO2/m2/year was calculated for the whole land region from 32°30' to 36°24' N latitude, 134°30' to 137°06' E longitude with an area of 3.94×104 km2.
Web Image Annotation Based on the Decision Rules Inferred by the Statistical Analysis of Web Pages
Authors: Joohyoun Park, Giseok Choe, Jongwon Lee, Jongho Nang
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

This paper proposes a rule based web image annotation method which improves the precision and recall of annota- tion by the use of decision tree. This decision tree learns the relationship between images and their annotations based on the proposed 17 attributes that specify the structural rela- tionship between them in HTML documents and the visual characteristics of the images. By converting and pruning this learned tree, a set of rules with high estimated accu- racy which determines whether or not a word can be the keyword of an image can be generated. Upon experimental results, the proposed method made 57 rules and the preci- sion and recall of annotation by these rules were about 88% and 95% for the various concepts, respectively. We argue the contribution of this work in two aspects. First, we sug- gest the clear criteria for precise annotation inferred by the statistical analysis of many web pages. Second, to cope with the deterioration of recall caused by the lack of measure for the visual characteristics, the visual similarity between an image and its concept combines to the attributes that used for tree learning.
Reduction of Complexity and Automation of Parallel Execution through Loop Level Parallelism
Authors: Robert A. Tefft, Roger Y. Lee
Venue: Proceedings of the Seventh International Conference on Quality Software (2007)

SIMD (Single Instruction Multiple Data) is a processor architecture classification from Flynn's taxonomy. The concept is that a single instruction set operates on multiple units of data simultaneously. Computers use this processor architecture are known as array processors or vector processors. Most computers in use today are SISD (single instruction single data) though allowing a single instruction to operate on multiple data can also be applied to a virtual machine that is capable of parallel execution through the use of multi-threading/multi-core processors, or distributed parallel execution on a multi-computer grid. This paper proposes a language structure that applies the SIMD concept to the Java virtual machine. The motive is to reduce the complexity of the code and ease implementation of parallelization by running a single set of instructions concurrently on an entire collection of objects. Index Terms Concurrency control, Parallel languages, Parallel processing, Parallel programming, Parallelizing compilers, Vector processing