ppxscal/embedding_network huggingface dataset:
Multi-focus Image Fusion Based on Stationary Wavelet Transform and Extended Spatial Frequency Measurement
Authors: Pusit Borwonwatanadelok, Wirat Rattanapitak, Somkait Udomhunsakul
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

In this paper, we propose a multi-focus image fusion approach based on Stationary Wavelet Transform (SWT) and extended the Spatial Frequency Measurements (SFM). Our proposed approach, two fused images are firstly decomposed into four subbands, which are one approximation subband (LL) and three details subbands (HL, LH and HH). Next, each subband is partitioned into blocks and each block is identified the clearer regions by computing the focus measure using the extended Spatial Frequency Measurement (SFM). Finally, the recovered fused image is reconstructed by performing the Inverse Stationary Wavelet Transform. From the experimental results, we found that the proposed method outperforms the traditional Wavelet Transform and SFM based methods in terms of objective and subjective assessments.
Fpga-based face detection system using Haar classifiers
Authors: Junguk Cho, Shahnam Mirzaei, Jason Oberg, Ryan Kastner
Venue: Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays (2009)

This paper presents a hardware architecture for face detection based system on AdaBoost algorithm using Haar features. We describe the hardware design techniques including image scaling, integral image generation, pipelined processing as well as classifier, and parallel processing multiple classifiers to accelerate the processing speed of the face detection system. Also we discuss the optimization of the proposed architecture which can be scalable for configurable devices with variable resources. The proposed architecture for face detection has been designed using Verilog HDL and implemented in Xilinx Virtex-5 FPGA. Its performance has been measured and compared with an equivalent software implementation. We show about 35 times increase of system performance over the equivalent software implementation.
Pulse shape adaptivity in OFDM/OQAM systems
Authors: Jinfeng Du, Svante Signell
Venue: Proceedings of the 2008 International Conference on Advanced Infocomm Technology (2008)

Adaptation is crucial to realise high data rate transmission in multicarrier communication systems over dispersive channels. Apart from rate/power adaptation enabled by orthogonal frequency division multiplexing (OFDM), OFDM/offset QAM (OFDM/OQAM) systems provide possibility to adjust pulse shapes depending on the channel characteristics. In this paper we discuss and evaluate pulse shape adaptivity in OFDM/OQAM systems with focus on the extended Gaussian functions (EGF) which have been shown to be good candidates for pulse shape adaptation. By investigating the time frequency dispersion robustness and carrier frequency offset sensitivity, both analysis and simulation results show that pulse shape adaptation with respect to the channel state information can improve the system performance.
Efficient triangular type-2 fuzzy logic systems
Authors: Janusz T. Starczewski
Venue: International Journal of Approximate Reasoning (2009)

In this study, an efficient fuzzy logic system (FLS) based on triangular type-2 fuzzy sets is designed. In detail, this paper provides a new method for computational complexity reduction in t-norm operations extended on triangular type-2 fuzzy sets. It is demonstrated that our approximate extended t-norms for arguments with triangular membership functions (MFs) satisfy axiomatics of the type-2 t-norm. A new efficient approximate iterative procedure based on the K-M type-reduction is proposed in order to develop triangular type-2 FLSs. The utility of triangular type-2 FLSs in approximate reasoning is illustrated by numerical examples.
Two-Dimensional Packet Classification and Filter&#x00a0;Conflict&#x00a0;Resolution in the Internet
Authors: Christian Gla&#x00df;er, Stephen Travers
Venue: Theory of Computing Systems (2009)

In this paper, we study the packet classification problem and the filter conflict resolution problem, both motivated by applications in the routing of packets in an IP network. For the first problem, we focus on the static 2-dimensional conflict-free (i.e., nested) filters. We design a linear space data structure with O(T w (n)+(log&#x2009;log&#x2009;n)2) query time on a RAM with word size O(w) bits where n is the number of filters in the router, w is the number of bits in an IP address and $$T_{w}(n)=O\biggl(\min\biggl\{\log w,\frac{\log w\log\log n}{\log\log w},\sqrt{\frac{\log n}{\log\log n}}\biggr\}\biggr).$$ that is definable in the e-model, either $\mathrm{coUP}\subseteq\mathcal{C}$or $\mathcal{C}\subseteq\mathrm{NP}$. For the existing models, gap theorems, where they exist at all, only identify gaps for the definability by regular languages. We prove gaps for the general case, i.e., for the definability by arbitrary languages. We obtain such general gaps for NP, coNP, 1NP, and&#x00a0;co1NP. For the regular case we prove further gap theorems for &#x03a3;2P, &#x03a0;2P, and &#x0394;2P. These are the first gap theorems for &#x0394;2P. This work is related to former work by Bovet, Crescenzi, and Silvestri, Vereshchagin, Hertrampf et al., Burtschick and Vollmer, and Borchert et al.
Artificial intelligence assessment of sea salt contamination of medium voltage insulators
Authors: D. S. Oikonomou, T. I. Maris, L. Ekonomou
Venue: Proceedings of the 8th conference on Systems theory and scientific computation (2008)

Sea salt contamination of overhead medium voltage insulators is the most common cause to outages in power systems installed in coastal regions. The contamination level of insulators is generally expressed by the equivalent salt deposit density (ESDD), which is the parameter that is taken into account, from almost every electric utility to diagnose the sea salt pollution severity on insulators. The periodic maintenance of insulators, which means the insulator washing, can reduce or even prevent the outages caused by the sea salt contamination. The maintenance scheduling is planned based on ESDD measurements, a process quite expensive and time consuming. The current work presents a new approach for the ESDD assessment based on artificial intelligence and more specifically artificial neural networks (ANN). A new ANN model capable to predict with accuracy the ESDD values is developed and is applied on operating medium voltage insulators presented results similar to the experimental ones. The proposed approach can be useful in the work of electrical maintenance engineers reducing maintenance time and cost.
An extended secret sharing scheme for colour images with fixed pixel expansion
Authors: Rabia Sirhindi, Mehreen Afzal, Saeed Murtaza
Venue: International Journal of Electronic Security and Digital Forensics (2009)

An extended visual secret sharing scheme uses multiple innocent-looking cover images to hide a secret image such that none discloses any portion of the secret. In this article, an extended secret sharing technique is proposed that shares a secret colour image in a couple of significant images using a fixed pixel expansion factor of 9 for a colour space as large as comprising 224, i.e. 16 million colours approximately. Furthermore, the data hiding technique employed in this article uses all three planes of a colour image which reduces the number of cover images that would otherwise be needed. Recovery is performed through a simple stacking (XOR) operation and a sequence of random integers.
Image Enlargement by Nonlinear Frequency Extrapolation with Morphological Operators
Authors: Masayuki Shimizu, Makoto Nakashizuka, Youji Iiguni
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

In this paper, we propose an image enlargement method by using morphological operators. Our enlargement method is based on the nonlinear frequency extrapolation method (Greenspan et al., 2000) by using a Laplacian pyramid image representation. In this method, the sampling process of input images is modeled as the Laplacian pyramid. A high resolution image is obtained with the finer scale Laplacian that is extrapolated by a nonlinear operation from a low resolution Laplacian. In this paper, we propose a novel nonlinear operation for extrapolation of the finer scale Laplacian. Our nonlinear operation is realized by morphological operators and is capable of generating the finer scale Laplacian, the amplitude of which is proportional to contrasts of edges that appear in the low resolution image. In experiments, the enlargement results given by the proposed method are demonstrated. Compared with the Greenspan's method, the proposed method can recover sharp intensity transients of image edges with small artifacts.
Machine-Generated Multimedia Content
Authors: Nathan Nichols, Kristian Hammond
Venue: Proceedings of the 2009 Second International Conferences on Advances in Computer-Human Interactions (2009)

In this paper we describe an automated system, and its attendant set of techniques and tools, that is able to generate novel multimedia experiences. Using existing online sources, external textual and multimedia repositories, and user preferences, the system builds a customized audio/visual experience for the user. We discuss one application in detail: News at Seven, an automatically generated, personalized news show. Beginning with a set of user preferences, the system is able to find relevant text, process that text, and supplement it with images, video, and blogger responses. The final output of the system is an online Flash presentation that uses animated avatars with generated speech and is modeled after traditional nightly news broadcast. We see this work as the beginning of an overall approach to machine-generated content.
High performance protein sequence database scanning on the Cell Broadband Engine
Authors: Adrianto Wirawan Bertil Schmidt Huiliang Zhang Chee Keong Kwoh
Venue: Scientific Programming (2009)

The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel multicore accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the Cell Broadband Engine can be used as a computational platform to accelerate two approaches for protein sequence database scanning: exhaustive and heuristic. We present efficient parallelization techniques for two representative algorithms: the dynamic programming based Smith-Waterman algorithm and the popular BLASTP heuristic. Their implementation on a Playstation &reg;3 leads to significant runtime savings compared to corresponding sequential implementations.
Utilizing Multi Agent Simulation to Explore Cities
Authors: Jinfeng Ma, Feng Mao, Wensheng Zhou
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

Cities are complex systems, with many dynamically changing parameters and large numbers of discrete actors. The heterogeneous nature of cities, make it difficult to generalize localized problems from that of city-wide problems. Computer modeling is becoming an increasingly important tool when examining how cities operate. Agent-based models allow for testing of different hypotheses and theories for urban change, thus leading to a greater understanding of how cities work. This paper propose a multi-agents systems/simulation model based on integration among parallel processing, coupling with vector GIS,temporal logic analysis,multi-objective evolution optimization and the integration with the rule engine. The efficiency of our approach is shown through some experimental results, which highlights how different theories can be incorporated into one model and demonstrates how the well-known principle that local action can give rise to global pattern but also how such pattern emerges as the consequence of positive feedback and learned behavior.
Tactile feedback for predictive text entry
Authors: Mark D. Dunlop, Finbarr Taylor
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

Predictive text entry provides a fast way to enter text on phones and other small devices. Early work on predictive text entry highlighted that the reaction time for checking the screen dominates text entry times. Improving accuracy of predictions brings a downside: as prediction gets better, users will drop the slow operation of checking the screen and will thus miss prediction errors and system feedback/suggestions. In this note, we present an experiment into the use of vibration to alert the user when word completion is likely to aid them, using a dynamic approach based on their current typing speed, and when there are no dictionary matches to their entry. Results show significantly faster entry rates for users with vibration alerts, raising speeds from 20wpm to 23wpm once practiced.
Employing aspect composition in adaptive software systems: a case study
Authors: Mazeiar Salehie, Sen Li, Ladan Tahvildari
Venue: Proceedings of the 1st workshop on Linking aspect technology and evolution (2009)

Adaptive software is a closed-loop system which aims at adjusting itself at runtime in different situations. Such a system needs a set of sensors to monitor attributes of itself and its operating environment. Furthermore, it requires a set of effectors in order to make changes in its entities. These changes are essential for fulfilling system's non-functional and functional requirements. Aspect-Oriented Programming (AOP) is a promising way to develop these sensors and effectors through static and dynamic composition of advices. This paper presents the experience of employing aspect composition in engineering a sample adaptive software. The main objectives are exploring the difficulties of utilizing this approach, and investigating the effectiveness of aspect-based adaptation actions. A J2EE bookstore application, TPC-W, was selected as the case study, to instrument sensors by the aid of static aspects, and effectors using dynamic aspects. The findings are promising, and encourage us to continue this line of research for more complex systems.
Introduction to modeling and generating probabilistic input processes for simulation
Authors: Michael E. Kuhl, Emily K. Lada, Natalie M. Steiger, Mary Ann Wagner, James R. Wilson
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Techniques are presented for modeling and generating the univariate probabilistic input processes that drive many simulation experiments. Emphasis is on the generalized beta distribution family, the Johnson translation system of distributions, and the B&eacute;zier distribution family. Also discussed are nonparametric techniques for modeling and simulating time-dependent arrival streams using nonhomogeneous Poisson processes. Public-domain software implementations and current applications are presented for each input-modeling technique. Many of the references include live hyperlinks providing online access to the referenced material.
Peak Shaving through Resource Buffering
Authors: Amotz Bar-Noy, Matthew P. Johnson, Ou Liu
Venue: Approximation and Online Algorithms: 6th International Workshop, WAOA 2008, Karlsruhe, Germany, September 18-19, 2008. Revised Papers (2009)

We introduce and solve a new problem inspired by energy pricing schemes in which a client is billed for peak usage. At each timeslot the system meets an energy demand through a combination of a new request, an unreliable amount of free source energy (e.g. solar or wind power), and previously received energy. The added piece of infrastructure is the battery, which can store surplus energy for future use. More generally, the demands could represent required amounts of energy, water, or any other tenable resource which can be obtained in advance and held until needed. In a feasible solution, each demand must be supplied on time, through a combination of newly requested energy, energy withdrawn from the battery, and free source. The goal is to minimize the maximum request. In the online version of this problem, the algorithm must determine each request without knowledge of future demands or free source availability, with the goal of maximizing the amount by which the peak is reduced. We give efficient optimal algorithms for the offline problem, with and without a bounded battery. We also show how to find the optimal offline battery size, given the requirement that the final battery level equals the initial battery level. Finally, we give efficient H n -competitive algorithms assuming the peak effective demand is revealed in advance, and provide matching lower bounds.
Modeling and simulation of integrated intelligent systems
Authors: Yongchang Li, Michael Balchanos, Bassem Nairouz, Neil Weston, Dimitri Mavris
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Complex systems consist of a large number of entities with their independent local rules and goals, along with their interactions. The effect of these properties tends to produce complex behaviors that are required to be understood in order to analyze and design the systems. However, these behaviors are difficult to be predicted a priori, and can only be studied through simulation. The study presented in this paper proposes a process for developing an integrated dynamic modeling and simulation environment designed for understanding the behavior of the next generation naval ship which is envisioned to be self-sensing, self-assessing and self-reacting. Various models, including power model, fluid model and control model, are developed to investigate the functionalities of the naval ship systems. An object oriented approach is employed to validate the architectural design of the integrated simulation environment and a surrogate modeling technique is utilized to accelerate the simulation speed.
Super-Exponential Size Advantage of Quantum Finite Automata with Mixed States
Authors: Rūsiņš Freivalds
Venue: Proceedings of the 19th International Symposium on Algorithms and Computation (2008)

Quantum finite automata with mixed states are proved to be super-exponentially more concise rather than quantum finite automata with pure states. It was proved earlier by A.Ambainis and R.Freivalds that quantum finite automata with pure states can have exponentially smaller number of states than deterministic finite automata recognizing the same language. There was a never published "folk theorem" proving that quantum finite automata with mixed states are no more than super-exponentially more concise than deterministic finite automata. It was not known whether the super-exponential advantage of quantum automata is really achievable.We use a novel proof technique based on Kolmogorov complexity to prove that there is an infinite sequence of distinct integers n such that there are languages L n in a 4-letter alphabet such that there are quantum finite automata with mixed states with 2n + 1 states recognizing the language L n with probability $\frac{3}{4} $ while any deterministic finite automaton recognizing L n needs to have at least e O(n ln n) states.
Let your users do the testing: a comparison of three remote asynchronous usability testing methods
Authors: Anders Bruun, Peter Gull, Lene Hofmeister, Jan Stage
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

Remote asynchronous usability testing is characterized by both a spatial and temporal separation of users and evaluators. This has the potential both to reduce practical problems with securing user attendance and to allow direct involvement of users in usability testing. In this paper, we report from an empirical study where we systematically compared three methods for remote asynchronous usability testing: user-reported critical incidents, forum-based online reporting and discussion, and diary-based longitudinal user reporting. In addition, conventional laboratory-based think-aloud testing was included as a benchmark for the remote methods. The results show that each remote asynchronous method supports identification of a considerable number of usability problems. Although this is only about half of the problems identified with the conventional method, it requires significantly less time. This makes remote asynchronous methods an appealing possibility for usability testing in many software projects.
Prediction of surface roughness using artificial neural network in lathe
Authors: Şakir Taşdemir, Süleyman Neşeli, Ismail Saritaş, Süleyman Yaldiz
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

In this study, the effect of tool geometry on surface roughness has been investigated in universal lathe. Machining process has been carried out on AISI 1040 steel in dry cutting condition using various insert geometry at depth of cut off 0.5 mm. At the end of the cutting operation, surface roughness has been measured using MAHR M1 perthometer. After experimental study, to predict the surface roughness, an ANN has been modelled using the data obtained. Modelling of ANN; tool nose radius (r), approach angle (K), rake angle (Y), tool overhang (L) have been used. In this study, surface roughness (Ra) is output data. The ANN has been designed on PC by using Matlab 6.5 software. Comparison of the experimental data and ANN results by means of statistically t test show that there is no significant difference and ANN has been used confidently.
Quel(s) facteur(s) de diff&eacute;renciation interindividuelle dans l'utilisation d'un document hyperm&eacute;dia en contexte d'apprentissage?
Authors: Dorothée Fillet, Eric Jamet
Venue: Proceedings of the 20th International Conference of the Association Francophone d'Interaction Homme-Machine (2008)

A high level of learner control characterizes hypermedia learning environments. Hypermedia environments allow learners to build their own strategies by controlling the information sequencing and pace. However this degree of freedom doesn't benefit to all learners depending on interindividual differences such as level of prior knowledge. The study aims at examining the factors influencing the use of control functions in a hypermedia learning environment. In addition, we are interested in how using control functions has an impact on learning outcomes. Results indicate that controlling the environment increases the comprehension level for learners with a high prior knowledge level. Conversely, using control functions hinders the level of comprehension for learners with no or little prior knowledges. These findings suggest a need for further research concerning the development of adaptative hypermedia learning environments based on users prior knowledge level.
Static analysis for inference of explicit information flow
Authors: Yin Liu, Ana Milanova
Venue: Proceedings of the 8th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering (2008)

This paper proposes a new static analysis for inference of explicit information flow. The analysis is context-sensitive, cubic, and works both on complete programs and software components. We perform experiments on several Java components which show that the analysis is precise and practical. Thus, the analysis can be incorporated in program understanding and verification tools and help verify security properties in a light-weight, practical manner.