ppxscal/embedding_network huggingface dataset:
Effect of plasma operation pressure on burn-in efficiency of an SIP-PVD chamber
Authors: Yi-Chi Lin, Ming-Yen Li, Hsiao-Che Wu, Poyo Chuang, Cheng-Sung Huang
Venue: Microelectronic Engineering (2008)

The effect of the plasma operation pressure on the burn-in efficiency of a self-ionized-plasma (SIP) physical vapor deposition (PVD) system for growing TiN liner films was examined. The experiments in this study were designed to obtain the proper plasma operation pressure and to set up a simplified procedure for optimization of the productivity and yield. Our results indicated that the number of particles falling on the wafer started to decrease when increasing the burn-in plasma pressure above 10mTorr and a comparatively stable condition could be maintained at a high burn-in plasma pressure over 20mTorr. It is believed that the increase of Ar pressure can influence the plasma spatial distribution within the chamber, and thereby enable the plasma to eliminate the particle sources concealed in the chamber narrow space. By proper Ar pressure the conventional burn-in procedure could be simplified without changing the TiN film properties. The simplified burn-in method can not only enhance the front-end yield, but it can also benefit the cost and productivity for production line consideration.
Projective Transformations for Image Transition Animations
Authors: TzuYen Wong, Peter Kovesi, Amitava Datta
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

Transformation of image patches is a common requirement for 2D transition animations such as shape interpolation and image morphing. It is usually done by applying affine transformations to triangular patches. However, the affine transformation does not model the perspective transformation frequently found in images. Hence, such techniques can only produce approximate results and usually use an excessively large number of triangles to compensate for this shortcoming. This paper proposes the application of projective transformations on quadrilateral image patches as a solution to this problem. We address the issues of appropriate decomposition and interpolation of projective transformation matrices to produce a natural looking transition animation for a single quadrilateral as well as for shapes made up of multiple quadrilaterals.
On the production of anorexic plan diagrams
Authors: Harish D, Pooja N. Darera, Jayant R. Haritsa
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

A "plan diagram" is a pictorial enumeration of the execution plan choices of a database query optimizer over the relational selectivity space. We have shown recently that, for industrial-strength database engines, these diagrams are often remarkably complex and dense, with a large number of plans covering the space. However, they can often be reduced to much simpler pictures, featuring significantly fewer plans, without materially affecting the query processing quality. Plan reduction has useful implications for the design and usage of query optimizers, including quantifying redundancy in the plan search space, enhancing useability of parametric query optimization, identifying error-resistant and least-expected-cost plans, and minimizing the overheads of multi-plan approaches. We investigate here the plan reduction issue from theoretical, statistical and empirical perspectives. Our analysis shows that optimal plan reduction, w.r.t. minimizing the number of plans, is an NP-hard problem in general, and remains so even for a storage-constrained variant. We then present a greedy reduction algorithm with tight and optimal performance guarantees, whose complexity scales linearly with the number of plans in the diagram for a given resolution. Next, we devise fast estimators for locating the best tradeoff between the reduction in plan cardinality and the impact on query processing quality. Finally, extensive experimentation with a suite of multi-dimensional TPCH-based query templates on industrial-strength optimizers demonstrates that complex plan diagrams easily reduce to "anorexic" (small absolute number of plans) levels incurring only marginal increases in the estimated query processing costs.
Tuning of the Structure and Parameters of Dynamic Process Neural Network Using Improved Chaotic PSO
Authors: Guangbin Yu, Guixian Li, Xiangyang Jin, Yanwei Bai
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

This paper presents the tuning of the structure and parameters of a dynamic process neural network(DPNN) using a improved chaotic particle swarm optimization(ICPSO), the ICPSO approach is a method of combining the improved particle swarm optimization(IPSO), which has a powerful global exploration capability, with the chaotic strategy , which can exploit the local optima. By introduced a new strategy to the ICPSO, it will also be shown that the ICPSO performs better than the traditional PSO and GA based on some benchmark test functions. A PNN with switches introduce to links is proposed. By tuning the structure and improving the connection weights of PNN simultaneously, a partially connected PNN can be obtained. By doing this, it eliminates some ill effects introduced by redundant in features of PNN. An application example on Iris forecasting is given to show the merits of the improved DPNN using ICPSO.
Competing with IT: the role of shared IT-business understanding
Authors: Gautam Ray, Waleed A. Muhanna, Jay B. Barney
Venue: Communications of the ACM (2007)

Studying why some firms derive more competitive advantage and value than others using IT resources.
On the Convergence of a New Smoothing Levenberg-Marquardt Method for the Nonlinear Inequalities
Authors: Yubo He, Changfeng Ma
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

The least l_2-norm solution for a possibley inconsistent system of nonlinear inequalities is studied in this paper. By introducing a new smoothing function, the problem is ap- proximated by a family of parameterized optimization prob- lems with twice continuously differentiable objective func- tions. Then a smoothing Levenberg-Marquardt method are applied to solve the parameterized optimization problems. The global convergence of the proposed method are established under some weak conditions. Numerical results show that the methods perform well.
Model-based analysis of Chinese calligraphy images
Authors: Sam T. S. Wong, Howard Leung, Horace H. S. Ip
Venue: Computer Vision and Image Understanding (2008)

A lot of research and development have been done on producing Chinese fonts with smooth outlines and solid colouring for computer displays and printing. Existing Chinese fonts however are not able to reproduce or convey the aesthetic properties of the characters produced by calligraphers. Ip and Wong proposed a parameterised brush model called the Virtual Brush, which enables efficient representation and generation of Chinese calligraphic writings such that the rendering is scalable in resolution and allows high quality publishing. While other researchers always focus on synthesis, we are working as a pioneer on the reverse problem-calligraphic image analysis. Given a static calligraphic image, it is a labour-intensive task to construct a set of 3-D geometric and writing model parameters to obtain a dynamic representation. It is therefore desirable to develop an automated approach to estimate the Virtual Brush parameters from images of Chinese calligraphy. This paper describes a methodology of a statistical-based approach with image processing techniques for the automatic estimation of the set of Virtual Brush writing parameters, such as the properties of brush hair and variations of ink deposition along a stroke trajectory, directly from an image of calligraphic writing. With our proposed approach, raw digitalised images of Chinese calligraphic writings could be analysed automatically for storage and subsequent synthesis for high quality publishing of Chinese characters in different styles and calligraphic artwork.
Data Selection for Nonlinear Proximal Support Vector Machine
Authors: Qiu-ge Liu, Qing He, Zhong-zhi Shi
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

An incremental learning method based on a new nonlinear Proximal Support Vector Machine (PSVM) classifier was developed, which can be utilized in online learning efficiently. However the memory requirement of this method is proportional to the square of the size of the training data, which makes it impractical in large data set learning problem. In this paper a data selection method, which can select a small fraction of the entire dataset as "support vectors" of PSVM classifiers, is devised. We also proposed a framework for incremental learning using this data selection method. It maintains only a small fraction of a large data set before merging and processing it with new incoming data, which makes online large dataset learning problem solvable for nonlinear PSVM. Mathematical analysis and experimental results demonstrated the effectiveness of our proposed technique both in batch mode and in online learning situation.
Merging the local and global approaches to probabilistic satisfiability
Authors: Pierre Hansen, Sylvain Perron
Venue: International Journal of Approximate Reasoning (2008)

The probabilistic satisfiability problem is to verify the consistency of a set of probability values or intervals for logical propositions. The (tight) probabilistic entailment problem is to find best bounds on the probability of an additional proposition. The local approach to these problems applies rules on small sets of logical sentences and probabilities to tighten given probability intervals. The global approach uses linear programming to find best bounds. We show that merging these approaches is profitable to both: local solutions can be used to find global solutions more quickly through stabilized column generation, and global solutions can be used to confirm or refute the optimality of the local solutions found. As a result, best bounds are found, together with their step-by-step justification.
Non-negative Matrix-Set Factorization
Authors: Le Li, Yu-Jin Zhang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

Non-negative Matrix Factorization (NMF) is a recently developed, biologically inspired method for nonlinearly finding purely additive, sparse, linear, low-dimension representations of non-negative multivariate data to consequently make latent structure, feature or pattern in the data clear. Although it has been successfully applied in several research fields, it is confronted with three main problems, unsatisfactory accuracy, bad generality and high computational load, while the processed data appear as matrices. In this paper, a new method coined Non-negative Matrix-Set Factorization (NMSF) is developed to overcome the problems and an efficient, strictly monotonically convergent algorithm of NMSF is put forward. As opposed to NMF, NMSF directly processes original data matrices rather than vectorization results of them. Theoretical analysis and experimental results show that NMSF has higher accuracy, better generality and lower computational load than NMF.
The genetic algorithm fractal
Authors: Jenny Juliany, Michael D. Vose
Venue: Evolutionary Computation (1994)

The original schema theorem (an inequality) has been replaced by an equality that determines the expected next generation for a simple genetic algorithm. This has made possible the computation of the trajectory of expected next generations. Visualization of these evolutionary trajectories beginning from different initial populations has led to the discovery of fractal structures.
Exercises in Software Design
Authors: J. L. Bentley
Venue: IEEE Transactions on Software Engineering (1987)

Typical software engineering courses teach principles in lectures and readings, then apply them in the development of a single program (requiring several months). We recently taught a software engineering class that incorporated many smaller exercises (requiring several hours). The class was successful: students were able to experiment with a broad set of ideas, and make interesting mistakes without jeopardizing the grades of their development team. This paper describes some tools and techniques we taught, and suggests how they might be incorporated into typical software engineering classes.
Distributed Service Provisioning Using Stateful Anycast Communications
Authors: Tim Stevens, Joachim Vermeir, Marc De Leenheer, Chris Develder, Filip De Turck, Bart Dhoedt, Piet Demeester
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

Notwithstanding IP anycast's introduction in Internet standards dates back to 1993 and its more recent adoption in IPv6 standards, its use in production environments is limited to date. This is mainly because native IP anycast lacks routing scalability and does not support session-based communications, thereby limiting its applicability to single request-response services such as DNS. For this reason, we propose a transparent anycast overlay architecture that retains the strengths of native anycast and neutralizes above-mentioned limitations. The resulting proxy infrastructure unleashes the power of anycast by opening up new opportunities for transparent distributed service provisioning. Taking into account user demands, available resources, network overhead and anycast infrastructure costs, we provide nearoptimal heuristics for the placement of proxy nodes and dimensioning the infrastructure in large networks. We show that even modest overlay infrastructures, consisting of a small number of proxy routers, provide an effective stateful anycast solution where the detour via the proxy routers is negligible in terms of extra network load. Furthermore, simulation results illustrate that server state aggregation in the proxy nodes lessens control plane overhead, which contributes significantly to service robustness.
Automated Model-Based Configuration of Enterprise Java Applications
Authors: Jules White, Douglas C. Schmidt, Krzysztof Czarnecki, Christoph Wienands, Gunther Lenz, Egon Wuchner, Ludger Fiege
Venue: Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference (2007)

applications is complex and error-prone, involving multiple participants/roles and numerous configuration changes across multiple files, application server settings, and database decisions. This paper describes an approach to automated enterprise application configuration that uses a feature model, executes a series of probes to verify configuration properties, formalizes feature selection as a constraint satisfaction problem, and applies constraint logic programming techniques to derive a correct application configuration. To validate the approach, we developed a configuration engine, called Fresh, for enterprise Java appli- cations and conducted experiments to measure how effectively Fresh can configure the canonical Java Pet Store application. Our results show that Fresh reduces the number of lines of hand written XML code by up to 92% and the total number of configuration steps by up to 72%.
Performance Analyses of Factorization Based on Gaussian PDF In rECGA
Authors: Minqiang Li, David E. Goldberg, Kumara Sastry, Tian-Li Yu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

In this paper, facet analyses are made about the population sizing and sampling of the factorization based on Gaussian probability density function in the real-coded ECGA (rECGA) on the univariate and multivariate real-valued deceptive functions (URDF and MRDFi). The dynamics of the rECGA with single Gaussian pdf and mixture Gaussian pdf are described statistically. Experimental results illustrate that the rECGA with mixture Gaussian pdf has a scalability of sub-quadratic polynomial on the MRDFi, which indicates that it is applicable to large-scale decomposable optimization problems.
Distributed Power Control in Cellular Mobile Radio Systems with Time-Varying Link Gains
Authors: Andrey V. Savkin, Pubudu N. Pathirana
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

A simple decentralized power control algorithm for com- munication systems with mobile users and unknown nonlin- ear and time-varying link gains is proposed and studied. We prove that the proposed algorithm is exponentially con- verging. Furthermore, we show that the algorithm signif- icantly outperforms the well-known Foschini and Miljanic algorithm in the case of quickly moving mobile users.
The Interlisp Programming Environment
Authors: W. Teitelman
Venue: Computer (1981)

Integration, extensibility, and ease of modification made Interlisp unique and powerful. Its adaptations will enhance the power of the coming world of personal computing and advanced displays.
Enhancing Ontology Concept Design by Knowledge Discovery
Authors: Silvana Castano, Alfio Ferrara
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

In this paper, we propose a knowledge discovery-based approach to ontology concept design. In our approach, concept design is a stepwise activity which exploits ontology matching techniques in order to retrieve useful external concepts semantically related to the design at hand. This way, the resulting ontology knowledge space is open towards external knowledge sources, by complementing the ontology expert knowledge with domain knowledge stored in other external sources, such as other domain ontologies, web directories, and, in general, the semantic web.
Predictive user click models based on click-through history
Authors: Benjamin Piwowarski, Hugo Zaragoza
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Web search engines consistently collect information about users interaction with the system: they record the query they issued, the URL of presented and selected documents along with their ranking. This information is very valuable: It is a poll over millions of users on the most various topics and it has been used in many ways to mine users interests and preferences. Query logs have the potential to partially alleviate the search engines from thousand of searches by providing a way to predict answers for a subset of queries and users without knowing the content of a document. Even if the predicted result is at rank one, this analysis might be of interest: If there is enough confidence on a user's click, we might redirect the user directly to the page whose link would be clicked. In this paper, we present three different models for predicting user clicks, ranging from most specific ones (using only past user history for the query) to very general ones (aggregating data over all users for a given query). The former model has a very high precision at low recall values, while the latter can achieve high recalls. We show that it is possible to combine the different models to predict with high accuracy (over 90%) a high subset of query sessions (24% of all the sessions).
Autonomous pedestrians
Authors: Wei Shao, Demetri Terzopoulos
Venue: Graphical Models (2007)

We address the challenging problem of emulating the rich complexity of real pedestrians in urban environments. Our artificial life approach integrates motor, perceptual, behavioral, and cognitive components within a comprehensive model of pedestrians as individuals. Featuring innovations in these components, as well as in their combination, our model yields results of unprecedented fidelity and complexity for fully autonomous multihuman simulation in a large urban environment. We represent the environment using hierarchical data structures, which efficiently support the perceptual queries that influence the behavioral responses of the autonomous pedestrians and sustain their ability to plan their actions on local and global scales.
A Simulation-Based Approach for Fine-Grained Project Plan Analysis
Authors: Jian Dai, Qing Wang, Mingshu Li, Junchao Xiao, Dapeng Liu, M. Wasif, Li Ruan
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

Making plans are the integral part to control projects. However, in most case, due to unforeseen changes in software process, it is hard to attain both the complete and the fine-grained information of plan. In this paper we present a simulation based approach to support management planning in forecasting not only at project level but at the task level as well. Instead of assuming many factors to be static (including productivity), we treat them dynamically. In comparison to existing method, our approach gives two benefits: (i) Central analysis of human resource, which can really reveal the unforeseen changes, (ii) A fine-grained simulation to support, select and customize project plans in context to a specific project. Finally, by mean of an example from our prototype system we demonstrate that how our approach is conducive to fine-grained project plan analysis.
A Parallel Mechanism for Detecting Curves in Pictures
Authors: P. M. Merlin
Venue: IEEE Transactions on Computers (1975)

In Hough [1], Duda and Hart [2], and Griffith [3] procedures were proposed for detecting lines in pictures and in [2] Duda and Hart extended their method for more general algebraic curve, fitting. This correspondence shows how this method can be used to detect any given curve in a specific orientation. The procedure presented here con be easily implemented and can be efficiently implemented in a parallel machine.
A Hybrid Fuzzy LMS Neural Network Model for Determining Weights of Criteria in MCDM
Authors: Feng Kong, Hong-yan Liu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

A hybrid fuzzy LMS neural network model, with fuzzy numbers as inputs, is set up to determine the weights of each criterion of alternatives. The model can determine the weights of each criterion automatically, according to the time-series data of market, so that they are more objectively and accurately distributed. The model also has a strong self-learning ability so that calculations are greatly reduced and simplified. Further, decision maker's specific preferences for uncertainty also are considered in the model. Hence, this method can give revised results while taking into decision maker's subjective intensions for uncertainty preference. A numerical example is given to illustrate the method..
A case study of the rustock rootkit and spam bot
Authors: Ken Chiang, Levi Lloyd
Venue: Proceedings of the first conference on First Workshop on Hot Topics in Understanding Botnets (2007)

In this paper we present a case study of the steps leading up to the extraction of the spam bot payload found within a backdoor rootkit known as Backdoor.Rustock.B or Spam-Mailbot.c. Following the extraction of the spam module we focus our analysis on the steps necessary to decrypt the communications between the command and control server and infected hosts. Part of the discussion involves a method to extract the encryption key from within the malware binary and use that to decrypt the communications. The result is a better understanding of an advanced botnet communications scheme.