Miracle-dz/UniFAR-FTUs huggingface dataset:
User Interface Management Systems: Models and Algorithms

From the Publisher: This book brings together for the first time all major approaches to User Interface Management Systems (UIMS) development from a programmer's algorithmic perspective. The various models for describing dialogs and generating user interfaces are discussed within the framework of a general UIMS architecture. Extensive examples are included to reinforce the concepts presented and applications for each approach are described. This guide will provide professional programmers with a understanding of the algorithms necessary to implement UIMSs. Readers without a programming background can use this book without prior user interface experience.
Implementation of analog neural networks

The topics discussed are: architectures of analog neural networks; multilevel or analog DRAM synapses; and a continuous time neural network using a high performance multilevel DRAM system. Neural networks must be implemented in hardware to achieve real time performance. The size and performance of the synapse element play a critical role in the overall system performance. In addition, a long term analog memory circuit is critical for most analog neural network implementations. Dynamic refreshing schemes potentially allow very compact synapses with fast read and write operations, but are only achievable with state of the art analog VLSI design theories and techniques. The implementation described performs an 8 to 10 bit transmission of a dynamically stored value and a 2 MHz, successive approximation analog-to-digital (A/D) to digital-to-analog (D/A) converter. <<ETX>>
Techniques for Component-Based Software Architecture Optimization

Although Component-Based System (CBS) increases the efficiency of development and reduces the need for maintenance, but even good quality components could fail to compose good product if the composition is not managed appropriately. In real world, such as industrial automation domain, this probability is unacceptable because additional measures, time, efforts, and costs are required to minimize its impacts. Many general optimization approaches have been proposed in literature to manage the composition of system at early stage of development. This paper investigates recent approach es used to optimize software architecture. The results of this study are important since it will be used to develop an efficient optimization framework to optimize software architecture in next step of our ongoing research.
Power loss and local surface impedance associated with conducting rough interfaces

The increase of the working frequencies of electromagnetic wave circuits causes high transmission losses due to the roughness of the metal surfaces. To understand this phenomenon, we model a rough metal interface in the simplest manner, by periodic grooves of infinite length. Then the reduced two-dimensional problem is analyzed numerically by the equivalent source method. Two polarizations are treated separately: the H-wave case, in which the directions of grooves and current are perpendicular, and the E-wave case, in which they are parallel. Three cross-sectional shapes of the metal surface—rectangular, triangular, and semielliptical conductors—are selected for computing the power losses and local surface impedances. We observe how the shape and groove depth affect the above characteristics, and investigate the behavior of the numerical results physically by taking account of the field distributions. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 89(1): 1–10, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.20218
Intelligent Internal Stealthy Attack and its Countermeasure for Multicast Routing Protocol in MANET

Multicast communication of mobile ad hoc networks is vulnerable to internal attacks due to its routing structure and high scalability of its participants. Though existing intrusion detection systems (IDSs) act smartly to defend against attack strategies, adversaries also accordingly update their attacking plans intelligently so as to intervene in successful defending schemes. In our work, we present a novel indirect internal stealthy attack on a tree‐based multicast routing protocol. Such an indirect stealthy attack intelligently makes neighbor nodes drop their routing‐layer unicast control packets instead of processing or forwarding them. The adversary targets the collision avoidance mechanism of the Medium Access Control (MAC) protocol to indirectly affect the routing layer process. Simulation results show the success of this attacking strategy over the existing “stealthy attack in wireless ad hoc networks: detection and countermeasure (SADEC)” detection system. We design a cross‐layer automata‐based stealthy attack on multicast routing protocols (SAMRP) attacker detection system to identify and isolate the proposed attacker. NS‐2 simulation and analytical results show the efficient performance, against an indirect internal stealthy attack, of SAMRP over the existing SADEC and BLM attacker detection systems.
Rate-Distortion Based Video Compression: Optimal Video Frame Compression and Object Boundary Encoding

From the Publisher: The book contains a review chapter on video compression, a background chapter on optimal bit allocation and the necessary mathematical tools, such as the Lagrangian multiplier method and Dynamic Programming. These two introductory chapters make the book self-contained and a fast way of entering this exciting field. Rate-Distortion Based Video Compression establishes a general theory for the optimal bit allocation among dependent quantizers. The minimum total (average) distortion and the minimum maximum distortion cases are discussed. This theory is then used to design efficient motion estimation schemes, video compression schemes and object boundary encoding schemes. For the motion estimation schemes, the theory is used to optimally trade the reduction of energy in the displaced frame difference (DFD) for the increase in the rate required to encode the displacement vector field (DVF). These optimal motion estimators are then used to formulate video compression schemes which achieve an optimal distribution of the available bit rate among DVF, DFD and segmentation. This optimal bit allocation results in very efficient video coders. In the last part of the book, the proposed theory is applied to the optimal encoding of object boundaries, where the bit rate needed to encode a given boundary is traded for the resulting geometrical distortion. Again, the resulting boundary encoding schemes are very efficient. Rate-Distortion Based Video Compression is ideally suited for anyone interested in this booming field of research and development, especially engineers who are concerned with the implementation and design of efficient video compression schemes. It also represents a foundation for future research, since all the key elements needed are collected and presented uniformly. Therefore, it is ideally suited for graduate students and researchers working in this field.
Knowledge modelling and multi-agent simulation: application to flood risks

This article proposes a multi-agent approach to manage the agrarian, economic and hydrologic knowledge of an agricultural territory. The knowledge is distributed over groups of agents in conflict in an environment. The problem resolution environment consists of the different parcels to occupy, characterized by size, slope, sensitivity etc. A group of agents is associated to each type of culture. From an initial occupation of the ground, the agents seek possibilities of permutation among the parcels of the territory in order to minimize the flood risks without degrading the individual satisfactions of their groups. We present the results obtained on the watershed of Villers-Ecalles (Pays de Caux, France).
Designing Unique Products with Self-morphing Randomness

Background : As people’s needs for differentiation and identity are changing, it is necessary to search for alternatives to standardized mass production in product design. To overcome limitations of existing approaches, we investigated design methods applying randomness for designing unique products. Methods : Three research methods were adopted. First, to understand the nature of randomness in order to build a theoretical basis, we reviewed related works dealing with randomness in the art and design fields. Second, we proposed self-morphing randomness as a method for product and service system design. We also developed three design cases. Third, we evaluated the feasibility and impact of the proposed method through expert and focus group interviews. Results : Self-morphing randomness is a design method whereby functional fundamentals of a product are randomly used to create unique products. To show the feasibility in the design practice, we developed three products using the method: Lightmorph-Light lamp, Light-print-Light lamp, and Sound-print-Sound speaker. Through expert and user evaluation, we identified that self-morphing randomness offers value in terms of uniqueness, spontaneity, storytelling, and emotional experience. Conclusion : This paper presents opportunities for applying randomness in designing unique products as an alternative for mass production. As a new design method, selfmorphing randomness can help design practice and education. Products made using this method can contribute to satisfying customers’ needs for differentiation and the pursuit of identity.
Hybrid approach to classifying sky regions in natural images

Sky is among the semantic object classes frequently seen in photographs and useful for image understanding, processing, and retrieval. We propose a novel hybrid approach to sky detection; based on color and texture classification, region extraction, and physics motivated sky signature validation. Sky can be of many different types; clear blue sky, cloudy/overcast sky, mixed sky, and twilight sky, etc. A single model cannot correctly characterize all the various types of skies due to the large difference in physics and appearance associated with different sky types. We have developed a set of physics-motivated sky models to identify clear blue-sky regions and cloudy/overcast sky regions. An exemplar-based approach is to generate the initial set of candidate sky regions. Another data-derived model is subsequently used to combine the results for different sky types to form a more complete sky map. Extensive testing using more than 3000 (randomly oriented) natural images shows that our comprehensive sky detector is able to accurately recall approximately 96% of all sky regions in the image set, with a precision of about 92%. Assuming correct image orientation, the precision on the same set of images increases to about 96%.
Adaptive particle swarm optimization-based particle filter for tracking maneuvering object

Particle filter is a powerful tool for visual tracking based on Sequential Monte Carlo framework. However,it is faced with a fatal problem due to its suboptimal sampling mechanism in the importance sampling process and thus leads to the well-know sample impoverishment problem. Although last decade people have developed a lot resampling schemes to solve this problem, no one can be suitable for all situation. The standard PSO-PF algorithm, which applying particle swarm optimization algorithm into particle filter framework, is an excellent one of them. However, we found that the standard PSO-PF not suitable for tracking object with complicated motion model such as maneuvering object, which is moving with various motion state such as abrupt motion or mildly motion or even stand still. In this paper, we propose an algorithm, which we call it Adaptive Particle Swarm Optimization-Based Particle Filter(APSO-PF), to track the maneuvering object. Instead of constant parameters used in the standard PSO-PF, APSO-PF can adaptively change its parameters according to the motion state of the object and thus improve the tracking performance significantly. Experimental results show that our algorithm surpasses the standard PSO-PF on both robustness and accuracy.
W3-Miner: Mining Weighted Frequent Subtree Patterns in a Collection of Trees

Mining frequent tree patterns have many useful applications in XML mining, bioinformatics, network routing, etc. Most of the frequent subtree mining algorithms (i.e. FREQT, TreeMiner and CMTreeMiner) use anti-monotone property in the phase of candidate subtree generation. However, none of these algorithms have verified the correctness of this property in tree structured data. In this research it is shown that anti-monotonicity does not generally hold, when using weighed support in tree pattern discovery. As a result, tree mining algorithms that are based on this property would probably miss some of the valid frequent subtree patterns in a collection of trees. In this paper, we investigate the correctness of anti-monotone property for the problem of weighted frequent subtree mining. In addition we propose W3-Miner, a new algorithm for full extraction of frequent subtrees. The experimental results confirm that W3-Miner finds some frequent subtrees that the previously proposed algorithms are not able to discover. Keywords—Semi-Structured Data Mining, Anti-Monotone Property, Trees.
A Three Dimensional Dual-Time-Stepping Method for the Solution of the Unsteady Navier-Stokes Equations

A time-accurate flow solver for the two- and three-dimensional Reynolds-averaged Navier-Stokes equations has been developed. Up to now it is restricted to rigid body motions with three translational and rotational degrees of freedom. An implicit time discretization is used, and the resulting set of coupled non-linear equations is solved iteratively. This is accomplished using well proven convergence acceleration techniques for explicit schemes such as multigrid, residual averaging, and local time stepping, in order to achieve large computational efficiency in the calculation. The approach, known as dual-time stepping in literature, allows the physical time step to be chosen on the basis of accuracy rather than stability. The method is parallelized using the domain decomposition technique. Every processor of a computer or workstation cluster works on one or more blocks of the whole block structure. The communication.
Evaluation of search performance of bacterial evolutionary algorithm

The search performance of evolutionary algorithms (EAs) has been widely studied. Interactions between genes in a chromosome, called "epistasis", make the theoretical investigation difficult. The goal of this study is a mathematical analysis of the effects of bacterial mutation on a bacterial evolutionary algorithm (BEA). The NK-landscape problem is employed for the investigation of this analysis in this paper. The search ability of bacterial mutation is formulated and compared with those of conventional mutation operations. It is shown that the bacterial mutation surpasses conventional ones in search performance.
Single antenna GPS information based aircraft attitude redundancy

The use of the Global Positioning System (GPS) as a primary source of information for aircraft position determination is becoming a common occurrence as the availability of receivers has increased and their costs have decreased. In addition to providing backup attitude information, GPS outputs may also be useful for fault detection of anomalous behavior in inertial systems. This paper reports on analysis of real time single antenna GPS flight data for the purpose of evaluating its utility for detecting faults in inertial attitude instruments.
Online longitudinal survey research: viability and participation

This article explores the viability of conducting longitudinal survey research using the Internet in samples exposed to trauma. A questionnaire battery assessing psychological adjustment following adverse life experiences was posted online. Participants who signed up to take part in the longitudinal aspect of the study were contacted 3 and 6 months after initial participation to complete the second and third waves of the research. Issues of data screening and sample attrition rates are considered and the demographic profiles and questionnaire scores of those who did and did not take part in the study during successive time points are compared. The results demonstrate that it is possible to conduct repeated measures survey research online and that the similarity in characteristics between those who do and do not take part during successive time points mirrors that found in traditional pencil-and-paper trauma surveys.
LAPACK: A portable linear algebra library for high-performance computers

The goal of the LAPACK project is to design and implement a portable linear algebra library for efficient use on a variety of high-performance computers. The library is based on the widely used LINPACK and EISPACK packages for solving linear equations, eigenvalue problems, and linear least-squares problems, but extends their functionality in a number of ways. The major methodology for making the algorithms run faster is to restructure them to perform block matrix operations (e.g., matrix-matrix multiplication) in their inner loops. These block operations may be optimized to exploit the memory hierarchy of a specific architecture. The LAPACK project is also working on new algorithms that yield higher relative accuracy for a variety of linear algebra problems. <<ETX>>
Position-dependent friction compensation for ballscrew tables

This paper describes a compensation scheme for positional-dependent friction in ballscrew-type X-Y tables. Based on the observations of the experimental data the friction of the ball-screw table exhibits periodical behaviour with varying amplitudes upon different velocities. The friction profile function f/sub x/(x) can be determined by measuring the static friction in each position. The parameter of amplitude for scaling the friction profile is calculated in real time for friction compensation. This formulation is then applied to the friction observer developed by Hassig and Friedland (1991). The convergence of the modified friction compensator is proved and the simulation results demonstrate the ability of the proposed method.
Intrusion detection oriented distributed negative selection algorithm

The negative selection algorithm proposed by Forrest et al. (1994) is a very significant change detection algorithm based on the generation process of T-Cells process in biological system. But when negative selection algorithm is used in distributed intrusion detection, the first problem that we meet is how to distribute the detectors in all detection workstations. To resolve this problem, this paper proposed a novel distributed negative selection algorithm based on the original negative selection algorithm. The core of this distributed negative selection algorithm is the distributing strategy. Two kinds of distributing strategies, random distributing strategy and greedy distributing strategy are given. Then we compared the performance of random distributing strategy and greedy distributing strategy. The experimental results show that: (1) distributed negative selection algorithm can avoid the problem of single point failure, when a part of detection workstations fails, the detection rate does not descend quickly; and (2) when some detection workstations fail, greedy distributing strategy can maintain better detection rate than random distributing strategy.
MEMS-IMU Based Pedestrian Navigator for Handheld Devices

A typical problem with MEMS-IMU is that the orientation information of the inertial navigator degrades rapidly with time causing large error in position estimate. Pedestrian navigation provides ways to restrict navigation solution so that the error in position estimate grows at a lower rate. The object of this work is to create a pedestrian navigator using low cost MEMS inertial sensors. This type of system can extend the operation period of the GPS integrated navigation system in the unaided mode. This paper presents a new method to estimate the step lengths and the travelled distance using low cost MEMS inertial measurement unit. The sensor assembly consists of MEMS gyroscopes and accelerometers capable of 1 mrad/s and 0.7 mg rms noise levels, respectively, and also of magnetic compass and barometric altimeter. The pedestrian navigator has been realised and algorithms tested using MATLAB with real sensor data. The system implements footfall and motion state recognition from inertial measurements. IMU signals are fused with magnetic compass and barometer signals by applying Kalman filter. Step length estimations are made using acceleration measurements from a single handheld IMU. There is no need for a priori knowledge of the step length and the IMU doesn’t have to be fixed in any particular orientation. By applying this method INS operation in pedestrian navigation can be extended to several minutes without external aiding which is a critical issue for handheld devices. The longer the unaided operations of the INS the better the power consumption can be achieved. The pedestrian navigator shows improvement on navigation accuracy and power consumption of the integrated navigation system in an urban environment.
ALEX-supporting low-literacy adults through mobile computing

Basic literacy skills are fundamental building blocks of education, yet for a very large number of adults tasks such as understanding and using everyday items is a challenge. While research, industry, and policy-making is looking at improving access to textual information for low-literacy adults, the literacy-based demands of today's society are continually increasing. Although many community-based organizations offer resources and support to adults with limited literacy skills, current programs have difficulties reaching and retaining those that would benefit most from them. To address these challenges, the National Research Council of Canada is proposing a technological solution to support literacy programs and to assist low-literacy adults in today's information-centric society: ALEX© – Adult Literacy support application for EXperiential learning. ALEX© has been created together with low-literacy adults, following guidelines for inclusive design of mobile assistive tools. It is a mobile language assistant that is designed to be used both in the classroom and in daily life, in order to help low-literacy adults become increasingly literate and independent.
A Review of Routing Protocols in Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have emerged as a key technology for next-generation wireless networking. Routing is a key factor for transfer of packets from source to destination. Every routing protocol has its own advantages and disadvantages. So selection of routing protocol is important for any network. Learning about advantages and disadvantages of protocols help us to know the effective selection of routing protocol for a network. This paper mainly deals how a protocol behaves differently according to network topology changes.
A new time domain method for estimating acoustic attenuation of soft tissue

A time-domain method, called the envelope-peak (EP) method, was recently proposed for attenuation estimation in reflection. The method has high precision and low computational overhead. However, if the bandwidth of the transmitted ultrasound pulse is very wide, the method can produce a biased estimate. The EP method is modified by preprocessing the echo signal using a split-spectrum technique. The combination of this technique with the narrowband technique enables the accuracy of the attenuation estimation to be well controlled without precise knowledge of the spectral shape and parameters of the transmitted pulse. Analysis shows that, while improving the accuracy of the attenuation estimation, the modified method retains the high precision of the original method. <<ETX>>