ppxscal/embedding_network huggingface dataset:
The Research and Application on Process Planning Knowledge Discovery Technology Based on Knowledge Model in Discrete Manufacturing Enterprise
Authors: Xiaoliang Jia, Zhenming Zhang, Xitian Tian
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

With the development of knowledge economy, knowledge resource in manufacturing enterprise has become the strategic resource. The competition in manufacturing enterprises focuses on the development and management of knowledge resource. CAPP (Computer Aided Processing Planning) system is the supportable system in process planning information for discrete manufacturing enterprise. The systematic methods of process planning knowledge discovery about professional knowledge, experience and criterion in process planning work become the key problem in CAPP system. Process planning knowledge model is analyzed oriented process planning knowledge discovery problem in CAPP system. Process planning knowledge discovery technology based on knowledge model driving is researched and is applied in CAPPFramework system (a CAPP development platform supported by 863/CIMS in China). The practical application of knowledge discovery technology in CAPPFramework is described in detail, it can automatically achieve the knowledge in process planning database by the interaction with knowledge engineer.
Cyber Threat Trend Analysis Model Using HMM
Authors: Do Hoon Kim, Taek Lee, Sung-Oh David Jung, Hoh Peter In, Hee Jo Lee
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

Prevention is normally recognized as one of the best defense strategy against malicious hackers or attackers. The desire of deploying better prevention mechanisms has motivated many security researchers and practitioners, who are studies threat trend analysis models. However, threat trend is not directly revealed from the time-series data because the trend is implicit in its nature. Besides, traditional time-series analysis, which predicts the future trend pattern by relying exclusively on the past trend pattern, is not appropriate for predicting a trend pattern in dynamic network environments (e.g., the Internet). Thus, supplemental environmental information is required to uncover a trend pattern from the implicit (or hidden) raw data. In this paper, we propose Cyber Threat Trend Analysis Model using Hidden Markov Model (HMM) by incorporating the supplemental environmental information into the trend analysis.
Relationships between Window-based Real-time Constraints
Authors: Gang TU, Jun-lin LI, Fu-min YANG, Wei LUO
Venue: Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2007)

This paper analyses the computational relationships of two types of window-based real-time constraint, sliding and fixed window constraint. First, based on the definition of "strict harder, the paper gives out the computing system, making possible of precisely comparing or translating window constraints. The analyses on the constraints are helpful for arranging task scheduling. Thereby, a scheduling framework that is capable of adapting to the changing environment is presented next, it bases on the idea that trying to guarantee unsolvable constraints is not as good as adjusting them. The scheduling framework modulates real-time system by adjusting the constraints on tasks so as to fit the changed resources. Last, evaluation results are presented to show that the scheduling framework is efficient and can largely decrease the mean rate of missed constraints for real-time tasks.
Real-Time Rendering of Multi-View Images from a Single Image with Depth
Authors: Kyoungsu Oh, Hyowon Kim, Chulhan Lee, Hyunwoo Ki
Venue: Proceedings of the The 2007 International Conference Computational Science and its Applications (2007)

Image reprojection is a technique to generate novel images by projecting a reference image of an arbitrary view. Previous image reprojection methods often run on the CPU, but these approaches take high-cost for rendering. We present a real-time image reprojection method using the GPU entirely. From given a reference image and its depth image of the scene prerendered, we generate novel images at arbitrary view points without the original geometry data. We render a simple plane at a novel view, and for each pixel being rendered, we make a ray that faces the opposite direction of the view. Then, we transform the ray to reference image space and trace the ray through a depth image to find an intersection, using a recently proposed method. In our experience, we archived tens of frames per second and it was independent from the complexity of the scene.
Some selection criteria for nested binary choice models: a comparative study
Authors: Teresa Aparicio, Inmaculada Villanúa
Venue: Computational Statistics (2007)

This paper deals with the problem of choosing the optimum criterion to select the best of a set of nested binary choice models. Special attention is given to the procedures which are derived in a decision-theoretic framework, called model selection criteria (MSC). We propose a new criterion, which we call C 2, whose theoretical behaviour is compared with that of the AIC and SBIC criteria. The result of the theoretical study shows that the SBIC is the best criterion whatever the situation we consider, while the AIC and C 2 are only adequate in some cases. The Monte Carlo experiment that is carried out corroborates the theoretical results and adds others: finite sample behaviour and robustness to changes in some aspects of the data generating process. The classical hypothesis testing procedures LR and LM are included and compared with the three criteria of the MSC category.
H-Tree: A data structure for fast path-retrieval in rooted trees.
Authors: Akram Shehadi Saynez, Maria Josefa Somodevilla, Manuel Martin Ortiz, Ivo H. Pineda
Venue: Proceedings of the Eighth Mexican International Conference on Current Trends in Computer Science (2007)

When repeatedly searching on a Depth-First or Breath-First Search fashion, some nodes are visited many times, as every search requires to start at the root. By providing a way to arrange the data in a different manner and using a hash table as the primary data structure, it is possible to get average lookup times of a path, from the root to any node in constant time, although a disadvantage arises when looking at the memory needs of the approach. We propose a structure called H-Tree created to reduce the time to extract a path from a rooted tree.
The power of choice in random walks: An empirical study
Authors: Chen Avin, Bhaskar Krishnamachari
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

In recent years random-walk-based algorithms have been proposed for a variety of networking tasks. These proposals include searching, routing, self-stabilization, and query processing in wireless networks, peer-to-peer networks and other distributed systems. This approach is gaining popularity because random walks present locality, simplicity, low-overhead and inherent robustness to structural changes. In this work we propose and investigate an enhanced algorithm that we refer to as random walks with choice. In this algorithm, instead of selecting just one neighbor at each step, the walk moves to the next node after examining a small number of neighbors sampled at random. Our empirical results on random geometric graphs, the model best suited for wireless networks, suggest a significant improvement in important metrics such as energy consumption and the cover time and load-balancing properties of random walks. We also systematically investigate random walks with choice on networks with a square grid topology. For this case, our simulations indicate that there is an unbounded improvement in cover time even with a choice of only two neighbors. We also observe a large reduction in the variance of the cover time, and a significant improvement in visit load balancing.
Clustering for unsupervised relation identification
Authors: Benjamin Rosenfeld, Ronen Feldman
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Unsupervised Relation Identification is the task of automatically discovering interesting relations between entities in a large text corpora. Relations are identified by clustering the frequently co-occurring pairs of entities in such a way that pairs occurring in similar contexts end up belonging to the same clusters. In this paper we compare several clustering setups, some of them novel and others already tried. The setups include feature extraction and selection methods and clustering algorithms. In order to do the comparison, we develop a clustering evaluation metric, specifically adapted for the relation identification task. Our experiments demonstrate significant superiority of the single-linkage hierarchical clustering with the novel threshold selection technique over the other tested clustering algorithms. Also, the experiments indicate that for successful relation identification it is important to use rich complex features of two kinds: features that test both relation slots together ("relation features"), and features that test only one slot each ("entity features"). We have found that using both kinds of features with the best of the algorithms produces very high-precision results, significantly improving over the previous work.
A Process Improvement Approach to Improve Web Form Design and Usability
Authors: Sean Thompson, Torab Torabi
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

The research presented in this paper is an examination of how the concepts used in process improvement may be applied to a web form to improve design and usability. Although much research is being conducted in improving the security and usability in how users input information to web sites, the HTML form remains as the primary source of user-web input. Thus far, a "process" oriented approach has not been explored in the literature as a methodology to improve user input interfaces on the web. Our approach is focussed on capturing as much user data as possible and using the process improvement engine as a tool to extract knowledge from the data so that the web form can be improved in terms of usability, clarity, security and user assistance.
Virtual fish: visual evidence of connectivity in a master-planned urban community
Authors: Greg T. Young, Marcus Foth, Natascha Y. Matthes
Venue: Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces (2007)

The rapid densification of urban areas around the world offers exciting opportunities for new place-based artworks and locative media that aim at engaging, informing and entertaining members of local communities. In this paper, we introduce a design competition for concepts of interaction design which display visual evidence of connectivity in a master-planned community. This competition is based in and focuses on one of Brisbane's newly built inner urban renewal developments. Furthermore, we introduce the conceptual interaction design of one of the competition's winning entries, as well as its potential and its challenges to engage local residents in participation and exploration of place-based information and community media.
An Authentication Scheme Using Non-Commutative Semigroups
Authors: M. M. Chowdhury
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

We give a new two-pass authentication scheme, which is a generalisation of an authentication scheme of Sibert- Dehornoy-Girault based on the Diffie-Hellman conjugacy problem. Compared to the above scheme, for some parameters it is more efficient with respect to multiplications. We sketch a proof that our authentication scheme is secure.
An optimized protocol for mobile network authentication and security
Authors: Xun Yi, Eiji Okamoto, Kwok Yan Lam
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (1998)

Recent years have seen an explosive growth of interest in mobile networks that support the mobility. The mobility of users, the transmission of signals through open air and the requirement of low power consumption by a mobile user bring to a mobile network a large number of new security issues. In this paper, we propose an optimized protocol for mobile network authentication and security. The particular features of the new proposal are: (1) only a public parameter (a large prime p) and the public key of the certification authority (yca) is required knowledge for all network participants; (2) only a block cipher is used as both the secret-key encryption algorithm and the underlying cipher of the hash function.
S4 enriched multimodal categorial grammars are context-free
Authors: Andrew R. Plummer
Venue: Theoretical Computer Science (2007)

Bar-Hillel et al. [Y. Bar-Hillel, C. Gaifman, E. Shamir, On categorial and phrase structure grammars, Bulletin of the Research Council of Israel F (9) (1960) 1-16] prove that applicative categorial grammars weakly recognize the context-free languages. Buszkowski [W. Buszkowski, Generative capacity of non-associative Lambek calculus, Bulletin of the Polish Academy of Sciences: Mathematics 34 (1986) 507-518] proves that grammars based on the product-free fragment of the non-associative Lambek calculus NL recognize exactly the context-free languages. Kandulski [M. Kandulski, The equivalence of non-associative Lambek categorial grammars and context-free grammars, Zeitschrift fur Mathematische Logik und Grundlagen der Mathematik 34 (1988) 41-52] furthers this result by proving that grammars based on NL also recognize exactly the context-free languages. Jager [G. Jager, Residuation, structural rules and context freeness, Journal of Logic, Language and Information 13 (2004) 47-59] proves that categorial grammars based on NL@?, the non-associative Lambek calculus enriched with residuated modalities, weakly recognize exactly the context-free languages. We extend this result, proving that categorial grammars based on NL"S"4, the enrichment of NL@? by the axioms 4 and T, weakly recognize exactly the context-free languages.
Designing free software samples: a game theoretic approach
Authors: Christophe Faugère, Giri Kumar Tayi
Venue: Information Technology and Management (2007)

We develop a vertical differentiation game-theoretic model that addresses the issue of designing free software samples (shareware) for attaining follow-on sales. When shareware can be reinstalled, cannibalization of sales of the commercial product may ensue. We analyze the optimal design of free software according to two characteristics: the evaluation period allotted for sampling (potentially renewable) and the proportion of features included in the sample. We introduce a new software classification scheme based on the characteristics of the sample that aid consumer learning. We find that the optimal combination of features and trial time greatly depends on the category of software within the classification scheme. Under alternative learning scenarios, we show that the monopolist may be better off not suppressing potential shareware reinstallation.
Macro Implementation of a Structured Assembly Language
Authors: J. L. Reuss
Venue: IEEE Transactions on Software Engineering (1982)

The feasibility of using macros to compile a linear assembly language is well established. A cross assembler has been implemented, via macros, for an assembly language, SCRAM, which embodies high-level language features such as user-controlled symbol scope and nested DO and IF/THEN/ELSE control structutes. Difficulties arose in implementation primarily from the inconvenience of managing assembly-time data
A Comparison of Antialiasing Techniques
Authors: F. C. Crow
Venue: IEEE Computer Graphics and Applications (1981)

Three antialiasing techniques were applied to a scene of moderate complexity. Early results suggest that prefiltering is still the most computationally effective method.
Cascaded Bidirectional Recurrent Neural Networks for Protein Secondary Structure Prediction
Authors: Jinmiao Chen, Narendra Chaudhari
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2007)

Protein secondary structure (PSS) prediction is an important topic in bioinformatics. Our study on a large set of non-homologous proteins shows that long-range interactions commonly exist and negatively affect PSS prediction. Besides, we also reveal strong correlations between secondary structure (SS) elements. In order to take into account the long-range interactions and SS-SS correlations, we propose a novel prediction system based on cascaded bidirectional recurrent neural network (BRNN). We compare the cascaded BRNN against another two BRNN architectures, namely the original BRNN architecture used for speech recognition as well as Pollastri's BRNN that was proposed for PSS prediction. Our cascaded BRNN achieves an overall three state accuracy Q3 of 74.38\%, and reaches a high Segment OVerlap (SOV) of 66.0455. It outperforms the original BRNN and Pollastri's BRNN in both Q3 and SOV. Specifically, it improves the SOV score by 4-6%.
A method for group decision making with multi-granularity linguistic assessment information
Authors: Yan-Ping Jiang, Zhi-Ping Fan, Jian Ma
Venue: Information Sciences: an International Journal (2008)

This paper proposes a method to solve the group decision making (GDM) problems with multi-granularity linguistic assessment information. In the method, the multi-granularity linguistic information provided by experts is firstly expressed in the form of fuzzy numbers. In order to make the collective opinion close to each expert's opinion, a linear goal programming model is constructed to integrate the fuzzy assessment information and to directly compute the collective ranking values of alternatives without the need of information transformation. Then, a fuzzy preference relation on the pairwise comparisons of the collective ranking values of alternatives is constructed using the dominance possibility degree of the comparison between the fuzzy numbers. By applying a non-dominance choice degree to this fuzzy preference relation, the ranking of alternatives is determined and the most desirable alternative(s) is selected. An example is used to illustrate the applicability of the proposed method and its advantages.
A Door to State-of-the-Art High-Performance Computing
Authors: Arturo Ortiz-Tapia
Venue: IEEE Distributed Systems Online (2007)

A review of "High-Performance Computing: Paradigm and Infrastructure," Laurence T. Yang and Minyi Guo, eds.
A coarse-to-fine method for shape recognition
Authors: Hui-Xuan Tang, Hui Wei
Venue: Journal of Computer Science and Technology (2007)

In this paper the deformation invariant curve matching problem is addressed. The proposed approach exploits an image pyramid to constrain correspondence search at a finer level with those at a coarser level. In comparison to previous methods, this approach conveys much richer information: curve topology, affine geometry and local intensity are combined together to seek correspondences. In experiments, the method is tested in two applications, contour matching and shape recognition, and the results show that the approach is effective under perspective and articulated deformations.
Testing input validation in Web applications through automated model recovery
Authors: Hui Liu, Hee Beng Kuan Tan
Venue: Journal of Systems and Software (2008)

Input validation is essential and critical in Web applications. It is the enforcement of constraints that any input must satisfy before it is accepted to raise external effects. We have discovered some empirical properties for characterizing input validation in Web applications. In this paper, we propose an approach for automated recovery of input validation model from program source code. The model recovered is represented in a variant of control flow graph, called validation flow graph, which shows essential input validation features implemented in programs. Based on the model, we then formulate two coverage criteria for testing input validation. The two criteria can be used to guide the structural testing of input validation in Web applications. We have evaluated the proposed approach through case studies and experiments.
Identity-Based Cryptosystems for Enhanced Deployment of OSGi Bundles
Authors: Pierre Parrend, Samuel Galice, Stephane Frenot, Stephane Ubeda
Venue: Proceedings of the The International Conference on Emerging Security Information, Systems, and Technologies (2007)

The OSGi platform is designed to make Java soft- ware extensible at runtime. This undeniably presents a great interest in several domains like embedded plat- forms or enterprise application servers. However, se- curing the deployment of the OSGi components, or bundles, proves to be a major challenge. The current approach consists in digitally signing the bundles and certifying the signature through a Public Key Infras- tructure (PKI). We propose to replace this technology with an Identity-Based Cryptosystem, which provides both bet- ter performances and simplified key management. We present an infrastructure for initialization and use of Identity-Based Cryptography, and define the digital sig- nature of bundles using such a cryptographic scheme. Based on our implementation, we provide a comparison between classical PKI management and Identity-Based PKI Management. The proposed approach proves to support radical improvement in the key management process, especially in strongly asymmetric system such as OSGi-based Home Gateway, where a few providers publish services for millions of potential users.
Arbitrarily layered micro-facet surfaces
Authors: Andrea Weidlich, Alexander Wilkie
Venue: Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia (2007)

In this paper we present a method to combine several micro-facet based surface layers into a single unified, expressive BRDF model that is easy to use. The restriction to micro-facet based layers constitutes no loss of generality, since both perfectly specular and perfectly diffuse surfaces can be seen as limit cases of the micro-facet approach. Such multi-layered surfaces can be used to re-create the appearance of a wide range of different materials, and yield good results without having to perform explicit sub-surface scattering computations. This is achieved through suitable approximations and simplifications of the scattering within the simulated layered surface, while still taking absorption and total internal reflection into account. We also discuss the corresponding probability distribution function that is needed for sampling purposes, and investigate how the flexibility of this new approach is best put to use.
TDML: A Data Mining Language for Transaction Databases
Authors: A. Muthukumar, R. Nadarajan
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

A desired feature of data mining systems is the ability to support ad hoc and interactive data mining in order to facilitate flexible and effective knowledge discovery. Data mining query languages can be designed to support such a feature. There are data mining query languages like DMQL for mining relational databases. In this paper, we have proposed a new data mining language for mining transaction databases called TDML. This proposed language mines association rule mining and sequential pattern mining. It uses a new bit map processing approach with buffered storage of results. Various types of data mining approaches that are supported like generalized mining, multilevel mining, multidimensional mining, distributed mining, partition mining, incremental mining, online mining, merge mining, transaction reduction, stream mining and targeted itemset mining.