ppxscal/embedding_network huggingface dataset:
Optimisation of a thin epitaxial Si layer as Ge passivation layer to demonstrate deep sub-micron n-and p-FETs on Ge-on-insulator substrates
Authors: B. De Jaeger, R. Bonzom, F. Leys, O. Richard, J. Van Steenbergen, G. Winderickx, E. Van Moorhem, G. Raskin, F. Letertre, T. Billon, M. Meuris, M. Heyns
Venue: Microelectronic Engineering (2005)

A key challenge in the engineering of Ge MOSFETs is to develop a proper Ge surface passivation technique prior to high-k dielectric deposition to obtain low interface state density and high carrier mobility. In this work, we optimise a thin, epitaxially grown, Si layer for this purpose. HfO2 is used as the high-k dielectric. With CV and TEM analysis, it is shown that the Si thickness must be controlled within a few monolayers to obtain a high-quality, defect free Ge - HfO2 interfacial layer. Ge deep sub-micron n-and p-FET devices fabricated with this technique yield promising device characteristics.
Computing All Immobilizing Grasps of a Simple Polygon with Few Contacts
Authors: Jae-Sook Cheong, Herman J. Haverkort, A. Frank van der Stappen
Venue: Algorithmica (2006)

We study the output-sensitive computation of all the combinations of edges and concave vertices of a simple polygon that allow an immobilizing grasp with less than four frictionless point contacts. More specifically, if n is the number of edges, and m is the number of concave vertices of the polygon, we show how to compute: in O(m4/3 log1/3 m + K) time, all K combinations that allow a form-closure grasp with two contacts; in O(n2 log4 m + K) time, all K combinations that allow a form-closure grasp with three contacts; in O(n log4 m + (nm)2/3 log2+&#x03b5; m + K) time (for any constant &#x03b5; > 0), all K combinations of one concave vertex and one edge that allow a grasp with one contact on the vertex and one contact on the interior of the edge, satisfying Czyzowicz's weaker conditions for immobilization; in O(n2 log3 n + K) time, all K combinations of three edges that allow a grasp with one contact on the interior of each edge, satisfying Czyzowicz's weaker conditions for immobilization.
University computing as a political process
Authors: Richard Wiste
Venue: ACM SIGSOC Bulletin (1975)

The various activities engaged in by those involved in computing can be looked upon from a number of perspectives. A choice of psychological, economic, geographic, political, or other perspectives may be made either on largely heuristic grounds or on grounds more closely tied to serious argument concerning the proper conduct of the activity under discussion. The choice of perspective embodied in this paper was made largely on the latter grounds. The basic argument is that, for many purposes, computing should be looked upon as a political process. If it were looked upon in this way, many things might be done otherwise, and the changes would be decidedly for the better. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Receptive field optimization for ensemble encoding
Authors: M. Abdelbar, O. Hassan, A. Tagliarini, Sridhar Narayan
Venue: Neural Computing and Applications (2006)

Ensemble encoding is a distributed data representation scheme that uses multiple, overlapping receptive fields to encode inputs to MLP networks. The number, placement, and form of the receptive fields can have a significant impact on the effectiveness of ensemble encoding. We present four approaches, two based on descriptive statistics, and two based on clustering, for optimizing receptive field configuration, and compare their performance on three benchmark data sets. To ensure fairness of comparison and reduce the effects of random noise, leave-one-out cross-validation is employed, and, a test of statistical significance is applied to the results.
Trust building with explanation interfaces
Authors: Pearl Pu, Li Chen
Venue: Proceedings of the 11th international conference on Intelligent user interfaces (2006)

Based on our recent work on the development of a trust model for recommender agents and a qualitative survey, we explore the potential of building users' trust with explanation interfaces. We present the major results from the survey, which provided a roadmap identifying the most promising areas for investigating design issues for trust-inducing interfaces. We then describe a set of general principles derived from an in-depth examination of various design dimensions for constructing explanation interfaces, which most contribute to trust formation. We present results of a significant-scale user study, which indicate that the organization-based explanation is highly effective in building users' trust in the recommendation interface, with the benefit of increasing users' intention to return to the agent and save cognitive effort.
Computational Anatomy for Generating 3D Avatars and Boosting Face Recognition Systems
Authors: M. Vaillant, G. Zang, J. Aliperti, N. Santhanam, S. Doucette, B. Hoffman, M. I. Miller
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

In this paper we present results of an automated system for generating 3D avatars from one or more photographs. We are motivated by the need to support pose and lighting correction for invariant facial identification. Our approach is to extend techniques from the now well established Computational Anatomy field to accommodate the projective geometry associated with video imagery. We present the general Compuational Anatomy framework, describe its merger with and application to the projective geometry setting, and present validation results on FRGC EXP 1.0.1, FRGC EXP 1.0.4, and FERET databases. In particular, we find sub-degree bias in rigid motion accuracy for avatar generation, and 1/20 eye distance average errors in feature landmark accuracy.
Providing information from the environment for growing electronic circuits through polymorphic gates
Authors: Michal Bidlo, Lukas Sekanina
Venue: Proceedings of the 2005 workshops on Genetic and evolutionary computation (2005)

This paper deals with the evolutionary design of programs (constructors) that are able to create (n+2)-input circuits from n-input circuits. The growing circuits are composed of polymorphic gates considered as building blocks. Therefore, the growing circuit can specialize its functionality according to environment which is sensed through polymorphic gates. The work was performed using a simple circuit simulator. We evolved constructors that are able to create arbitrarily large polymorphic even/odd parity circuits and polymorphic sorting networks.
A Formal Specification for Web Services Composition and Verification
Authors: Yuliang Shi, Liang Zhang, Bing Liu, Fangfang Liu, Lili Lin, Baile Shi
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

Due to the promising features of web services, their deployment and research are booming. Among them, various techniques for web service composition have been developed. In this paper, we propose a new composition framework. We use automata to describe behaviors of web services. Each of underlying web services can interact with others through asynchronous messages passing according to its interaction role (client or server). All these messages are recorded by a virtual global observer and the observation result is just the composition conversation of web services. We also develop a formal a top-down verification mechanism on this framework and provide some realizable conditions for a successful composition.
Mutual relevance feedback for multimodal query formulation in video retrieval
Authors: Arnon Amir, Marco Berg, Haim Permuter
Venue: Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval (2005)

Video indexing and retrieval systems allow users to find relevant video segments for a given information need. A multimodal video index may include speech indices, a text-from-screen (OCR) index, semantic visual concepts, content-based image features, audio features and more. Formulating an efficient multimodal query for a given information need is much less intuitive and more challenging for the user than of composing a text query in document search. This paper describes a video retrieval system that uses mutual relevance feedback for multimodal query formulation. Through an iterative search and browse session, the user provides relevance feedback on system's output and the system provides the user a mutual feedback which leads to better query and better retrieval results. Official evaluation at the NIST TRECVID 2004 Search Task is provided for both Manual and Interactive search. It is shown that in the Manual task the queries result from the mutual feedback on the training data significantly improve the retrieval performances. A further improvement over the manual search is achieved in the interactive task by using both browsing and mutual feedback on the test set.
Approximate fixed-rank closures of covering problems
Authors: Daniel Bienstock, Mark Zuckerberg
Venue: Mathematical Programming: Series A and B (2006)

Consider a 0/1 integer program min{cTx :Ax&#x2265;b, x &#x2208; {0,1}n} where A is nonnegative. We show that if the number of minimal covers of Ax&#x2265;b is polynomially bounded, then for any &#x03b5;>0 and any fixed q, there is a polynomially large lift-and-project relaxation whose value is at least (1&#x2212;&#x03b5;) times the value of the rank &#x2264;q relaxation. A special case of this result is that given by set-covering problems, or, generally, problems where the coefficients in A and b are bounded.
Guidelines for Designing and Developing Contents for Mobile Learning
Authors: Antonella Grasso, Teresa Roselli
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

The learning benefits deriving from the use of mobile technologies in in-field research and professional training have been demonstrated by a number of initiatives worldwide. Because learning can occur in highly variable places and conditions, the choice of mobile device and an accurate analysis of the target users are essential during the design phase of Mobile Learning applications, to identify the user scenarios and various possible experiences deriving from use of the system. The present work reconstructs previous experiences in the field of designing contents for Mobile Learning, with the aim of gleaning clear guidelines for designing and implementing highly efficacious, usable contents and courses for mobile devices. These guidelines were applied to create a course on the work of Caravaggio, to be studied using a handheld device.
An object-based video coding framework for video sequences obtained from static cameras
Authors: Asaad Hakeem, Khurram Shafique, Mubarak Shah
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

This paper presents a novel object-based video coding framework for videos obtained from a static camera. As opposed to most existing methods, the proposed method does not require explicit 2D or 3D models of objects and hence is general enough to cater for varying types of objects in the scene. The proposed system detects and tracks objects in the scene and learns the appearance model of each object online using incremental principal component analysis (IPCA). Each object is then coded using the coefficients of the most significant principal components of its learned appearance space. Due to smooth transitions between limited number of poses of an object, usually a limited number of significant principal components contribute to most of the variance in the object's appearance space and therefore only a small number of coefficients are required to code the object. The rigid component of the object's motion is coded in terms of its affine parameters. The framework is applied to compressing videos in surveillance and video phone domains. The proposed method is evaluated on videos containing a variety of scenarios such as multiple objects undergoing occlusion, splitting, merging, entering and exiting, as well as a changing background. Results on standard MPEG-7 videos are also presented. For all the videos, the proposed method displays higher Peak Signal to Noise Ratio (PSNR) compared to MPEG-2 and MPEG-4 methods, and provides comparable or better compression.
Channel Capacity of TDD-OFDM-MIMO for Multiple Access Points in a Wireless Single-Frequency-Network
Authors: Y. Takatori, F. Fitzek, K. Tsunekawa, R. Prasad
Venue: Wireless Personal Communications: An International Journal (2005)

The multiple-input-multiple-output (MIMO) technique is the most attractive candidate to improve the spectrum efficiency in the next generation wireless communication systems. However, the efficiency of MIMO techniques reduces in the line of sight (LOS) environments. In this paper, we propose a new MIMO data transmission scheme, which combines Single-Frequency-Network (SFN) with TDD-OFDM-MIMO applied for wireless LAN networks. In our proposal, we advocate to use SFN for multiple access points (MAP) MIMO data transmission. The goal of this approach is to achieve very high channel capacity in both LOS and non line of sight (NLOS) environments. The channel capacity of the proposed method is derived for the direct path environments and it confirms the effectiveness of the proposed scheme in the LOS scenario. Moreover, solid computer simulation results confirm the effectiveness of the proposed method in both, single user and multiuser scenarios.
Regular grammars with truth values in lattice-ordered monoid and their languages
Authors: Li Sheng, Yongming Li
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

In this study, we introduce the concept of lattice-valued regular grammars. Such grammars have become a necessary tool for the analysis of fuzzy finite automata. The relationship between lattice-valued finite automata (LA) and lattice-valued regular grammars (LRG) are discussed and we get the following results, for a given LRG, there exists an LA such that they accept the same languages, and vice versa. We also show the equivalence between deterministic lattice-valued regular grammars and deterministic lattice-valued finite automata.
Compound Classification Models for Recommender Systems
Authors: Lars Schmidt-Thieme
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Recommender systems recommend products to customers based on ratings or past customer behavior. Without any information about attributes of the products or customers involved, the problem has been tackled most successfully by a nearest neighbor method called collaborative filtering in the context, while additional efforts invested in building classification models did not pay off and did not increase the quality. Therefore, classification methods have mainly been used in conjunction with product or customer attributes. Starting from a view on the plain recommendation task without attributes as a multi-class classification problem, we investigate two particularities, its autocorrelation structure as well as the absence of re-occurring items (repeat buying). We adapt the standard generic reductions 1-vs-rest and 1-vs-1 of multi-class problems to a set of binary classification problems to these particularities and thereby provide a generic compound classifier for recommender systems. We evaluate a particular specialization thereof using linear support vector machines as member classifiers on MovieLens data and show that it outperforms state-of-the-artmethods, i.e., item-based collaborative filtering.
Adaptive filtering algorithms with error normalization
Authors: Zayed M. Ramadan
Venue:  (2005)

This dissertation deals, in general, with adaptive filtering and presents several least mean-square (LMS)-type algorithms that could be used in many adaptive filtering applications like system identification, noise cancellation, channel equalization, and signal prediction. The aim is to improve the performance of these applications by minimizing the mean-square error, increasing the rate of convergence, and improving the tracking capability of the proposed adaptive algorithms. In addition, the research work in this dissertation introduces an adaptive noise canceller for solving the signal leakage or crosstalk problem. Two proposed LMS-type algorithms, based mainly on error normalization, are analyzed and simulated in system identification using different cases of correlated and uncorrelated input data in stationary and nonstationary environments. Simulation results show significant improvements of the proposed algorithms over other algorithms in achieving higher rates of convergence with the same value of steady-state mean-square error. Two more algorithms are analyzed and simulated in adaptive noise cancellation using real speech signals. The first one is a time-varying step-size algorithm that employs both data and error normalization in its update recursion. The second algorithm uses a step-size that varies in time between two hard limits based on a predetermined nonlinear decreasing function of signal to noise ratio (SNR) estimated at every iteration. Simulation results of these algorithms show their superior performance over other algorithms in minimizing signal distortion and reverberation in the recovered speech. Finally, a new adaptive noise canceller is proposed to improve the system performance in the presence of crosstalk or signal leakage in the reference input. The proposed adaptive noise canceller consists of three microphones and two adaptive filters that automatically adjust their coefficients through LMS-type algorithms to produce an output that is as close as possible to the original speech signal. Simulation results in both stationary and nonstationary noise environments show significant improvements of this proposed adaptive noise canceller over the conventional one.
Current Research and Use of Anomaly Detection
Authors: Kalle Burbeck
Venue: Proceedings of the 14th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprise (2005)

Anomaly detection in IP networks, detection of deviations from what is considered normal, is an important complement to misuse detection based on known attack descriptions. Anomaly detection is at present time often implemented to some extent in available intrusion detection products. Still much effort is spent on anomaly detection research and many problems remains to be explored. Performing anomaly detection in real-time places hard requirements on the algorithms used. First, to deal with the massive data volumes one needs to have efficient data structures and indexing mechanisms. Secondly, the dynamic nature of today's information networks makes the characterization of normal requests and services difficult. What is considered as normal during some time interval may be classified as abnormal in a new context, and vice versa. These factors make many proposed data mining techniques less suitable for real-time intrusion detection.
Tight lower bounds for certain parameterized NP-hard problems
Authors: Jianer Chen, Benny Chor, Mike Fellows, Xiuzhen Huang, David Juedes, Iyad A. Kanj, Ge Xia
Venue: Information and Computation (2005)

Based on the framework of parameterized complexity theory, we derive tight lower bounds on the computational complexity for a number of well-known NP-hard problems. We start by proving a general result, namely that the parameterized weighted satisfiability problem on depth-t circuits cannot be solved in time nO(k)mO(1), where n is the circuit input length, m is the circuit size, and k is the parameter, unless the (t - 1)- st level W[t-1] of the W-hierarchy collapses to FPT. By refining this technique, we prove that a group of parameterized NP-hard problems, including weighted sat, hitting set, set cover, and feature set, cannot be solved in time no(k)mO(1), where n is the size of the universal set from which the k elements are to be selected and m is the instance size, unless the first level W[1] of the W-hierarchy collapses to FPT. We also prove that another group of parameterized problems which includes WEIGHTED q-SAT (for any fixed q ≥ 2), CLIQUE, INDEPENDENT SET, and DOMINATING SET, cannot be solved in time no(k) unless all search problems in the syntactic class SNP, introduced by Papadimitriou and Yannakakis, are solvable in subexponential time. Note that all these parameterized problems have trivial algorithms of running time either nkmO(1) or O(nk).
Random Projection-Based Multiplicative Data Perturbation for Privacy Preserving Distributed Data Mining
Authors: Kun Liu Hillol Kargupta
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

This paper explores the possibility of using multiplicative random projection matrices for privacy preserving distributed data mining. It specifically considers the problem of computing statistical aggregates like the inner product matrix, correlation coefficient matrix, and Euclidean distance matrix from distributed privacy sensitive data possibly owned by multiple parties. This class of problems is directly related to many other data-mining problems such as clustering, principal component analysis, and classification. This paper makes primary contributions on two different grounds. First, it explores Independent Component Analysis as a possible tool for breaching privacy in deterministic multiplicative perturbation-based models such as random orthogonal transformation and random rotation. Then, it proposes an approximate random projection-based technique to improve the level of privacy protection while still preserving certain statistical characteristics of the data. The paper presents extensive theoretical analysis and experimental results. Experiments demonstrate that the proposed technique is effective and can be successfully used for different types of privacy-preserving data mining applications.
Experience in using business scenarios to assess COTS components in integrated solutions
Authors: Sharon Lymer, WenQian Liu, Steve Easterbrook
Venue: Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research (2005)

Constructing software by integrating commercial off-the-shelf (COTS) components is widely practised, particularly in the IT service industry. For vendors of COTS components, requirements engineering is particularly challenging. To continually improve their products, vendors must identify and analyze problems that occur when their components are used in a wide variety of integrated solutions, and they must anticipate new applications in which their components could be used. In this paper, we describe a scenario-based framework developed at the Software Group division of IBM Corporation (IBM SWG) The framework mimics the solution integration process for new business opportunities, allowing the development teams to evaluate their components, discover and re-solve integration issues, and to surface new requirements for future releases. This paper describes the framework, gives an example of its use in a business scenario, discusses the experience of using this framework at IBM SWG, and relates the lessons learned.