ppxscal/embedding_network huggingface dataset:
Fabrication of carbon nanotube arrays for field emission and sensor devices by nanoimprint lithography
Authors: Lei Yin, Hongzhong Liu, Yucheng Ding, Hongbo Lan, Bingheng Lu
Venue: Microelectronics Journal (2009)

This work brings forth the idea of incorporating insulation in the resist used for ultraviolet (UV) curing nanoimprint lithography (NIL). Carbon nanotubes (CNTs) are grown in the space between two insulated resist patterns on the conductive substrate to make CNTs arrays. Two imprinting processes, soft UV curing NIL with DRPPR process and novel NIL without cured residual resist, are presented to achieve the insulation patterns. First the fabricating process is performed using a polydimethylsiloxane (PDMS) stamp. Subsequently, inductively coupled plasma (ICP) is essential to wipe off the residual resist film. To avoid the ICP process, a novel UV curing NIL is presented. Its special hard quartz stamp with chrome shelter can protect the residual resist film out of curing during the UV exposure process, and the uncured resist can be easily removed by ultrasonic vibration in organic solutions. The CNT arrays are prepared on the patterned substrates by the pyrolysis of iron phthalocyanine (FePc). Field emission experiments reveal that the turn-on field of those CNTs arrays is low to 1.3V/um.
Self-organization of unattended wireless acoustic sensor networks for ground target tracking
Authors: Jinsong Zhang, Malaka Walpola, David Roelant, Hao Zhu, Kang Yen
Venue: Pervasive and Mobile Computing (2009)

A distributed, self-organization algorithm for ground target tracking using unattended acoustic sensor network is developed. Instead of using microphone arrays, each sensor node in the sensor network uses only a single microphone as its sensing device. This design can greatly reduce the size and cost of each sensor node and allow more flexible deployment of the sensor network. The self-organization algorithm presented in this paper can dynamically select proper sensor nodes to form the localization sensor groups that can work as a virtual microphone array to perform energy efficient target localization and tracking. To achieve this, we use a time-delay based bearing estimation plus triangulation for source localization in the sensor network. Major error sources of the localization method like time delay estimation, bearing calculation and triangulation are analyzed and sensor selection criteria are developed. Based on these criteria and neighborhood information of each sensor node, a distributed self-organization algorithm is developed. Simulation results show the effectiveness of the proposed algorithm.
Cluster based evolving FCBR for flow time prediction in semiconductor manufacturing factory
Authors: Chen-Hao Liu, Pei-Chann Chang, I-Wei Kao
Venue: Proceedings of the 8th conference on Applied computer scince (2008)

In this research, a hybrid approach by combining Self-Organizing Map (SOM) and Evolving Fuzzy Case-Based Reasoning (EFCBR) for flow time prediction is proposed. Genetic Algorithms (GAs) is applied to fine-tune the fuzzy term numbers and weights of fuzzy features in the CBR model. The flow time and related shop floor status are collected and fed into the SOM for classification. Then, corresponding EFCBR is applied for flow time prediction. The effectiveness of the proposed method (SEFCBR) is shown by comparing with other approaches.
Optimum Channel Allocation in OFDMA Multi-cell Systems
Authors: Andrea Abrardo, Paolo Detti, Gaia Nicosia, Andrea Pacifici, Mara Servilio
Venue: Network Control and Optimization: Second Euro-NF Workshop, NET-COOP 2008 Paris, France, September 8-10, 2008. Revised Selected Papers (2009)

This paper addresses the problem of allocating users to radio resources (i.e., sub-carriers) in the downlink of an OFDMA cellular system. We consider a classical multi-cellular environment with a realistic interference model and a margin adaptive approach, i.e., we aim at minimizing total transmission power while maintaining a certain given rate for each user. We discuss computational complexity issues of the resulting model and present a heuristic approach that finds optima under suitable conditions, or "reasonably good" solutions in the general case. Computational experiences show that, in a comparison with a commercial state-of-the-art optimization solver, our algorithm is quite effective in terms of both infeasibilities and transmitted powers and extremely efficient in terms of CPU times.
Combination of modified BPNN algorithms and an efficient feature selection method for text categorization
Authors: Cheng Hua Li, Soon Cheol Park
Venue: Information Processing and Management: an International Journal (2009)

This paper proposes new modified methods for back propagation neural networks and uses semantic feature space to improve categorization performance and efficiency. The standard back propagation neural network (BPNN) has the drawbacks of slow learning and getting trapped in local minima, leading to a network with poor performance and efficiency. In this paper, we propose two methods to modify the standard BPNN and adopt the semantic feature space (SFS) method to reduce the number of dimensions as well as construct latent semantics between terms. The experimental results show that the modified methods enhanced the performance of the standard BPNN and were more efficient than the standard BPNN. The SFS method cannot only greatly reduce the dimensionality, but also enhances performance and can therefore be used to further improve text categorization systems precisely and efficiently.
Simulation optimization for industrial scheduling using hybrid genetic representation
Authors: Marcus Andersson, Amos H. C. Ng, Henrik Grimm
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Simulation modeling has the capability to represent complex real-world systems in details and therefore it is suitable to develop simulation models for generating detailed operation plans to control the shop floor. In the literature, there are two major approaches for tackling the simulation-based scheduling problems, namely dispatching rules and using meta-heuristic search algorithms. The purpose of this paper is to illustrate that there are advantages when these two approaches are combined. More precisely, this paper introduces a novel hybrid genetic representation as a combination of both a partially completed schedule (direct) and the optimal dispatching rules (indirect), for setting the schedules for some critical stages (e.g. bottlenecks) and other non-critical stages respectively. When applied to an industrial case study, this hybrid method has been found to outperform the two common approaches, in terms of finding reasonably good solutions within a shorter time period for most of the complex scheduling scenarios.
On Backward-Style Anonymity Verification
Authors: Yoshinobu Kawabe, Ken Mano, Hideki Sakurada, Yasuyuki Tsukada
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

Many Internet services and protocols should guarantee anonymity; for example, an electronic voting system should guarantee to prevent the disclosure of who voted for which candidate. To prove trace anonymity, which is an extension of the formulation of anonymity by Schneider and Sidiropoulos, this paper presents an inductive method based on backward anonymous simulations. We show that the existence of an image-finite backward anonymous simulation implies trace anonymity. We also demonstrate the anonymity verification of an e-voting protocol (the FOO protocol) with our backward anonymous simulation technique. When proving the trace anonymity, this paper employs a computer-assisted verification tool based on a theorem prover.
D&eacute;monstration: advene, un outil pour la lecture active audiovisuelle
Authors: Yannick Prié, Olivier Aubert, Bertrand Richard
Venue: Proceedings of the 20th International Conference of the Association Francophone d'Interaction Homme-Machine (2008)

The Advene project aims at providing a framework to practice active reading on audiovisual documents, through the annotation of the document and the visualisation of the annotations along user-defined modalities. It involves conceptual, technical and ergonomical issues, especially due to the dynamic nature of the annotated documents.
Defect prevention with orthogonal defect classification
Authors: Ajit Ashok Shenvi
Venue: Proceedings of the 2nd India software engineering conference (2009)

"Learning from the past" to make systems more efficient in terms of cost and time is the hallmark of any engineering discipline. Prevention of defects is the "holy grail" of "learning's from the past" i.e. every product generation we learn from our defects and prevent it from recurring in the next generation. Taking this philosophy further "capturing defects in the earlier stage of the life cycle" is a means of preventing defects in the later stages of the product life cycle. Correction of defects is costly and the cost increases exponentially with every subsequent stage. This also impacts the cycle-time directly. Defect prevention then not only helps in cost reduction but also helps in cutting down the development time. When we talk of software development, we are talking of hundreds of defects (in-process as well as post release). It would be very inefficient and time-consuming to have preventive action planning for each of them, as most of them could be symptoms of some common root cause. If we have to handle software defects of such large magnitude the best way then would be to classify them into patterns and then do root cause analysis on those patterns. There are number of methodologies available in the industry to do this classification and IBM's ODC (Orthogonal defect classification) is one such methodology. The methodology classifies each defect into orthogonal (mutually exclusive) attributes some technical and some managerial. These attributes provide all the information to be able to sift through the enormous volume of data and arrive at patterns on which root-cause analysis can be done. This coupled with good action planning and tracking can achieve high degree of defect reduction and cross learning. The questions always then are -- can methodologies be really applied to do software defect prevention in a structured way? How can an abstract defect classification mechanism really help to identify patterns? How does one measure the effectiveness of such actions? Who should do these activities? How does all this fit into the existing process framework? This paper is an attempt to answer these questions by sharing the experiences of using the IBM-ODC methodology in a case study of real-life software development project (DVD player product). The motivation of this paper is not to discuss the ODC methodology itself but rather to demonstrate through a case study, the structured process for defect prevention using some attributes of ODC for defect classification and its related interpretations for causal analysis, action planning and results tracking. The fitments of the scheme into the bigger picture of defect prevention, cross learning and mapping to elements of the SEI-CMMI framework are some of the highlights of this paper. The paper concludes with a summary of learning's and some points to ponder.
Distributed Fusion Method under Imperfect Channel in Wireless Sensor Networks
Authors: FanJiang Xu, ZhiTang Li, WeiMing Li
Venue: Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 01 (2009)

Wireless Sensor Networks have been widely developed in modern surveillance systems since its complementary and overlapping coverage on targets. In order to track and estimate the path of target, the sensor data should to be fused. However, the information fusion performance is influenced largely due to the presence of disruptions and delays in communication channels between sensor nodes which are not sufficiently solved until now. A stochastic estimation function is proposed in this paper to predict the fusion performance by adopting the effects of network connectivity and message delay into the fusion equations. Compared with the traditional deterministic estimation function, the final equations produced by the method consist of some prior parameters which can be determined according to the specific communication environment where the sensor networks are deployed. The simulation results have shown that the stochastic method can reduce the fusion time markedly in addition to provide good estimation capabilities.
The Complete Guide to Game Audio, Second Edition: For Composers, Musicians, Sound Designers, Game Developers (Gama Network Series), 2 edition
Authors: Aaron Marks
Venue:  (2008)

Turn your musical passion into a profitable career with this exhaustive, indispensable resource for game audio. Develop the business and technical skills you need to succeed in the multibillion dollar games industry. Step-by-step instructions lead you through the entire music and sound effects process-from developing the essential skills and purchasing the right equipment to keeping your clients happy. Create music and sound effects for games. Master the exacting specifications for composing music and creating sound effects on the various gaming platforms and systems. Technical considerations are explained in detail so that game audio professionals can make sense of complicated systems, learn about the highly involved programming elements, and create high quality audio without a hitch.This new edition includes:* Information on hot new next-generation game consoles - Xbox 360, PlayStation 3, Wii, Nintendo DS, and Sony PSP. * The companion DVD features audio and cinematic examples and sample business contracts. --Aaron Marks is a highly influential industry leader who remains active in all aspects of game audio. Marks won Best Game Audio Article, Publication or Broadcast - Game Audio Network Guild Awards - 2002; and he is also an award-winning composer and sound designer (2004 Game Tunnel - Best Sound in an Independent Game of the Year Award - I of the Enemy). His knowledge is sought after and can help any game audio specialist grow in his/her field.--Exhaustive, Indispensable resource for Game Audio - so that game audio professionals can do things like learn how to set up a studio, make a demo reel, find the work, bid on contracts, negotiate deals with clients and win the contracts.--Technical considerations explained in detail so that game audio professionals can make sense of complicated systems, learn about the highly involved programming elements, and create high quality audio without a hitch. --DVD includes audio samples, demos, interviews, and Dolby's latest Sound Development Kit so that game composers and sound designers can benefit quickly and easily by porting to their own work.
Automatic knot adjustment using an artificial immune system for B-spline curve approximation
Authors: Erkan ílker, Ahmet Arslan
Venue: Information Sciences: an International Journal (2009)

Reverse engineering transforms real parts into engineering concepts or models. First, sampled points are mapped from the object's surface by using tools such as laser scanners or cameras. Then, the sampled points are fitted to a free-form surface or a standard shape by using one of the geometric modeling techniques. The curves on the surface have to be modeled before surface modeling. In order to obtain a good B-spline curve model from large data, the knots are usually respected as variables. A curve is then modeled as a continuous, nonlinear and multivariate optimization problem with many local optima. For this reason it is very difficult to reach a global optimum. In this paper, we convert the original problem into a discrete combinatorial optimization problem like in Yoshimoto et al. [F. Yoshimoto, M. Moriyama, T. Harada, Automatic knot placement by a genetic algorithm for data fitting with a spline, in: Proceedings of the International Conference on Shape Modeling and Applications, IEEE Computer Society Press, 1999, pp. 162-169] and Sarfraz et al. [M. Sarfraz, S.A. Raza, Capturing outline of fonts using genetic algorithm and splines, in: Fifth International Conference on Information Visualisation (IV'01), 2001, pp. 738-743]. Then, we suggest a new method that solves the converted problem by artificial immune systems. We think the candidates of the locations of knots as antibodies. We define the affinity measure benefit from Akaike's Information Criterion (AIC). The proposed method determines the appropriate location of knots automatically and simultaneously. Furthermore, we do not need any subjective parameter or good population of initial location of knots for a good iterative search. Some examples are also given to demonstrate the efficiency and effectiveness of our method.
Nanofabrication, Nanoinstrumentation and Nanoassembly by Nanorobotic Manipulation
Authors: Toshio Fukuda, Masahiro Nakajima, Pou Liu, Haitham Elshimy
Venue: International Journal of Robotics Research (2009)

A nanolaboratory is proposed to realize the capabilities of nanofabrication, nanoinstrumentation and nanoassembly to make three-dimensional structures, devices and systems in the nanoworld. A nanorobotic manipulation system is introduced to realize these capabilities inside a scanning electron microscope or a transmission electron microscope. Some precursors are introduced into the small working space in the nanoworld, so that cutting, bending, peeling and fixing operations in the nanoworld could be realized using nanomanipulators, electron-bean-induced deposition and other methodologies as in the macroworld. After making the three-dimensional structures, the nanodevices such as nanosensors and nanoactuators are fabricated using carbon nanotubes and a focused ion beam chemical vapor deposition process. Some nanodevices for bioapplications are also presented.
Biomolecular computation based on cell communication
Authors: Jian-Qin Liu, Tadashi Nakano
Venue: Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems (2008)

In this paper, based on the signaling mechanism of phosphorylation and dephosphorylation, we have designed rewriting rules for graph automata by related pathways in kinase computing for 3-SAT problem solving in which linear complexity of control-space and time is derived to achieve efficiency in theory. This work is important for pathway design of autonomous kinase computation that has biological faithfulness.
Strong stability preserving hybrid methods
Authors: Chengming Huang
Venue: Applied Numerical Mathematics (2009)

This paper is concerned with the strong stability preserving (SSP) time discretizations for semi-discrete systems, obtained from applying the method of lines to time-dependent partial differential equations. We focus on the construction of explicit hybrid methods with nonnegative coefficients, which are a class of multistep methods incorporating a function evaluation at an off-step point. A series of new SSP methods are found. Among them, the low order methods are more efficient than some well known SSP Runge-Kutta or linear multistep methods. In particular, we present some fifth to seventh order methods with nonnegative coefficients, which have healthy CFL coefficients. Finally, some numerical experiments on the Burgers equation are given.
A concept and implementation of higher-level XML transformation languages
Authors: Daniel Foetsch, Elke Pulvermueller
Venue: Knowledge-Based Systems (2009)

In the software development (e.g. with product lines or refactoring) transformations play an increasing role. To ease and automate these transformations, we propose a solution based on the operator hierarchy concept. It allows to define transformation operator hierarchies containing different levels of transformation operators. The operators capture reusable knowledge units. The concrete realization of such a higher-level transformation language construction is demonstrated by an application of the XML operator hierarchy concept to the transformation language XSLT. XSLT serves as an example which is employed to provide the elementary transformation operators. On top of these elementary operators the layered concept allows the definition of new higher-level operators, e.g. domain-independent and domain-specific ones. In an application example the construction of the higher-level language XML2DSV is presented. This is a stand-alone domain-specific transformation language, which can be used to create delimiter-separated values (DSV) files from XML documents, on the base of XSLT. We developed XTC (XML Transformation Coordinator) to automate the multi-level transformation process.
Multilevel summation of electrostatic potentials using graphics processing units
Authors: David J. Hardy, John E. Stone, Klaus Schulten
Venue: Parallel Computing (2009)

Physical and engineering practicalities involved in microprocessor design have resulted in flat performance growth for traditional single-core microprocessors. The urgent need for continuing increases in the performance of scientific applications requires the use of many-core processors and accelerators such as graphics processing units (GPUs). This paper discusses GPU acceleration of the multilevel summation method for computing electrostatic potentials and forces for a system of charged atoms, which is a problem of paramount importance in biomolecular modeling applications. We present and test a new GPU algorithm for the long-range part of the potentials that computes a cutoff pair potential between lattice points, essentially convolving a fixed 3D lattice of ''weights'' over all sub-cubes of a much larger lattice. The implementation exploits the different memory subsystems provided on the GPU to stream optimally sized data sets through the multiprocessors. We demonstrate for the full multilevel summation calculation speedups of up to 26 using a single GPU and 46 using multiple GPUs, enabling the computation of a high-resolution map of the electrostatic potential for a system of 1.5 million atoms in under 12s.
Global Optimization through Rotation Space Search
Authors: Richard I. Hartley, Fredrik Kahl
Venue: International Journal of Computer Vision (2009)

This paper introduces a new algorithmic technique for solving certain problems in geometric computer vision. The main novelty of the method is a branch-and-bound search over rotation space, which is used in this paper to determine camera orientation. By searching over all possible rotations, problems can be reduced to known fixed-rotation problems for which optimal solutions have been previously given. In particular, a method is developed for the estimation of the essential matrix, giving the first guaranteed optimal algorithm for estimating the relative pose using a cost function based on reprojection errors. Recently convex optimization techniques have been shown to provide optimal solutions to many of the common problems in structure from motion. However, they do not apply to problems involving rotations. The search method described in this paper allows such problems to be solved optimally. Apart from the essential matrix, the algorithm is applied to the camera pose problem, providing an optimal algorithm. The approach has been implemented and tested on a number of both synthetically generated and real data sets with good performance.